This project begins from the simple premise that the task of endogenizing the NK search landscape can be done by representing the search environment as a binary bipartite network of M actors affiliating with N components. This bipartite network can be then be analyzed according to the Stochastic Actor-Oriented Model (SAOM) (Snijders, 1996).

Thus, the Stochastic Actor-Oriented MNK model, abbrivated SaoMNK, is designed for running strategic search simulation, testing, and experimentation by leveraging the RSiena package, an R implementation of
Simulation Investigation for Empirical Network Analysis (SIENA).

This tutorial offers a basic introduction to SaoMNK.

###############  Load R6 Class DEPENDENCIES ############################
## Biparite Environment Search Simulation Class
SaomNkRSienaBiEnv <- source(file.path(dir_r, 'SAOM_NK_R6_model.R'))$value
# ## RSiena search Class
# SaomNkRSienaBiEnv_search_rsiena <- source(file.path(dir_proj, 'SAOM_NK_R6_search_rsiena_model.R'))$value
## default settings: Users do not change; TODO: implment within restricted class attributes
DV_NAME <- 'self$bipartite_rsienaDV'
#
steps_per_actor <- 25

1. NO Endogenous Noise in Environment (Structural Effects = 0)

1.1 Environment Configuration

#
environ_params <- list(
  M = 12,       ## Actors
  N = 9,       ## Components
  BI_PROB = 0, ## Environmental Density (DGP hyperparameter)
  component_matrix_start = 'rand', ##**TODO** Implement: 'rand','modular','semi-modular',...
  rand_seed = 1234,
  plot_init = F,
  name = '_test_tutorial_nb_'
)
#
env1 <- SaomNkRSienaBiEnv$new(environ_params)
## 
## TEST FROM CALLED CLASS INIT *BEFORE* BASE INIT
## 
## CALLED _BASE_ INIT
## 
## TEST FROM CALLED CLASS INIT *AFTER* BASE INIT
print(c(env1$M, env1$N))
## [1] 12  9
library(Matrix)  # For block diagonal matrices
#
create_block_diag <- function(N, B) {
  # Determine the approximate block size
  block_sizes <- rep(N %/% B, B)  # Equal-sized blocks
  block_sizes[1:(N %% B)] <- if (N %% B == 0) {
    block_sizes[1:(N %% B)]   # Adjust for remainder
  } else {
    block_sizes[1:(N %% B)] + 1
  }
  # Create individual binary blocks
  blocks <- lapply(block_sizes, function(s) matrix(1, nrow = s, ncol = s))
  # Combine blocks into a block diagonal matrix
  block_diag_matrix <- as.matrix(bdiag(blocks))  # Convert sparse to standard matrix
  # Ensure exact NxN dimensions
  block_diag_matrix <- block_diag_matrix[1:N, 1:N]  # Trim to N x N
  # return
  return(block_diag_matrix)
}
# Example usage:
N <- 6  # Number of rows/columns
B <- 2  # Number of blocks
block_matrix <- create_block_diag(8, 2)
# Print the matrix
print(block_matrix)
##      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
## [1,]    1    1    1    1    0    0    0    0
## [2,]    1    1    1    1    0    0    0    0
## [3,]    1    1    1    1    0    0    0    0
## [4,]    1    1    1    1    0    0    0    0
## [5,]    0    0    0    0    1    1    1    1
## [6,]    0    0    0    0    1    1    1    1
## [7,]    0    0    0    0    1    1    1    1
## [8,]    0    0    0    0    1    1    1    1

1.2 Structrual Model

SAOM Objective Function serves as the stochastic actor’s utility function for strategic search.

#
strategies <- list(
  egoX   =   c(-1, 0, 1),
  inPopX =   c( 1, 0, -1)
)

## 2.b. Component Payoffs vector
set.seed(12345)
component_payoffs <-  runif(environ_params$N, min = 0, max = 1)
## 2. Strategies sets the objective function as a linear combination of network stats across DVs
#
actor_strats_list <- lapply(strategies, function(strat) rep(strat,  environ_params$M/length(strat)) )

component_int_mat <- create_block_diag(environ_params$N, round(environ_params$N/3))

# dyad_cov_XWX <- ( outer(component_payoffs, component_payoffs, '*') * 
#     create_block_diag(environ_params$N, round(environ_params$N/3))
# )

dyad_cov_X <- matrix(runif(n = environ_params$N*environ_params$M, min = -.5, max= 1), nrow=environ_params$M)
# dyad_cov_X <- matrix(runif(environ_params$N*environ_params$M) - runif(environ_params$N*environ_params$M), 
#                      nrow=environ_params$M) 

# dyad_cov_XWX_X <- t( dyad_cov_XWX %*% t(dyad_cov_X) )

#
structure_model <- list(
  dv_bipartite = list(
    name = 'self$bipartite_rsienaDV',
    effects = list( ##**STRUCTURAL EFFECTS -- dyadic/network endogeneity sources**
      list(effect='density', parameter= 0, dv_name=DV_NAME, fix=T ), ##interaction1 = NULL
      list(effect='inPop',   parameter= 0, dv_name=DV_NAME, fix=T ), #interaction1 = NUL
      list(effect='outAct',  parameter= 0, dv_name=DV_NAME, fix=T )
    ),
    ## COVARIATE EFFECTS
    coCovars = list( 
      ##** COMPONENTS : MONADIC CONSTANT COVARIATE EFFECTS **##
      # list(effect='altX',   parameter= 0, dv_name=DV_NAME, fix=T,
      #      interaction1='self$component_1_coCovar', x = component_payoffs 
      # ),
      # list(effect='outActX',   parameter= 0, dv_name=DV_NAME, fix=T,
      #      interaction1='self$component_1_coCovar', x = component_payoffs 
      # ),
      ##** STRATEGIES : MONADIC CONSTANT COVARIATE EFFECTS **##
      list(effect='egoX',   parameter= 0,  dv_name=DV_NAME, fix=T,
           interaction1='self$strat_1_coCovar',   x = actor_strats_list[[1]] 
      ), #interaction1 = NULL
      list(effect='inPopX', parameter= 0,  dv_name=DV_NAME, fix=T,
           interaction1='self$strat_2_coCovar',  x = actor_strats_list[[2]] 
      ) #,
      # list(effect='totInDist2', parameter= 0,  dv_name=DV_NAME, fix=T,
      #      interaction1='self$strat_3_coCovar',  x = (actor_strats_list[[1]] - actor_strats_list[[2]] )
      # )
    ),
    ##**MONADIC TIME-VARYING COVARIATE EFFECTS -- DYNAMIC STRATEGY PROGRAMS**
    varCovars = list(),
    ##**DYADIC CONSTANT COVARIATE EFFECTS -- EXOGENOUS INTERACTION MATRIX**
    coDyadCovars = list(
      list(effect='XWX',   parameter= 1, dv_name=DV_NAME, fix=T,
           interaction1='self$component_1_coDyadCovar',
           x = component_int_mat ## component-[actor]-component dyads
      ) ,
      list(effect='X',   parameter= 0, dv_name=DV_NAME, fix=T,
           interaction1='self$component_2_coDyadCovar',
           x = dyad_cov_X ## deltas = changes of payoff contributions from each actor-component
      )
    ),
     ##**DYADIC TIME-VARYING COVARIATE EFFECTS -- DYNAMIC INTERACTION MATRIX**
    varDyadCovars = list(),
    interactions = list(
      list(effect='egoX|XWX',   parameter= 0, dv_name=DV_NAME, fix=T,
           interaction1='self$strat_1_coCovar',
           interaction2='self$component_1_coDyadCovar'
      ),
      list(effect='inPopX|X',   parameter= 0, dv_name=DV_NAME, fix=T,
           interaction1='self$strat_2_coCovar',
           interaction2='self$component_2_coDyadCovar'
      )
    )
  )
)
env1$preview_effects(structure_model, filter=FALSE)
## $effect
## [1] "XWX"
## 
## $parameter
## [1] 1
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$component_1_coDyadCovar"
## 
## $x
##       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
##  [1,]    1    1    1    0    0    0    0    0    0
##  [2,]    1    1    1    0    0    0    0    0    0
##  [3,]    1    1    1    0    0    0    0    0    0
##  [4,]    0    0    0    1    1    1    0    0    0
##  [5,]    0    0    0    1    1    1    0    0    0
##  [6,]    0    0    0    1    1    1    0    0    0
##  [7,]    0    0    0    0    0    0    1    1    1
##  [8,]    0    0    0    0    0    0    1    1    1
##  [9,]    0    0    0    0    0    0    1    1    1
## 
## $effect
## [1] "X"
## 
## $parameter
## [1] 0
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$component_2_coDyadCovar"
## 
## $x
##              [,1]         [,2]        [,3]        [,4]       [,5]         [,6]
##  [1,]  0.98460541 -0.009871387  0.52275043 -0.01816299 -0.3794959  0.919646128
##  [2,] -0.44819685  0.948122985  0.05515619 -0.40970726  0.1532957  0.532530035
##  [3,] -0.27143976  0.561222816  0.04243836 -0.43481532 -0.1451293  0.258300585
##  [4,]  0.60352743  0.466813955  0.80319235 -0.41741927  0.6873517  0.059404367
##  [5,] -0.49829512  0.084742727  0.85623200  0.43831420 -0.1119735  0.003707558
##  [6,]  0.08680500  0.547815459  0.42613685  0.94670543  0.9789757 -0.427622971
##  [7,]  0.19374198  0.316086797 -0.29895255  0.74095430  0.6353106  0.428421309
##  [8,]  0.08221597 -0.160299232  0.67328992 -0.02745765  0.9696674  0.942170938
##  [9,]  0.10372771  0.226836633  0.14379823 -0.18046182 -0.1715782  0.482440764
## [10,] -0.23155462  0.689510755  0.89091096  0.59874418  0.9230608  0.265437987
## [11,]  0.92748813 -0.491018556  0.65986484  0.24886153 -0.2758131 -0.274852684
## [12,]  0.18059211 -0.218431331 -0.11047813  0.59465796  0.4005355  0.805671821
##              [,7]       [,8]        [,9]
##  [1,]  0.27166252  0.4013924  0.85375569
##  [2,] -0.48702813  0.5721698  0.45618165
##  [3,] -0.47120785  0.2707685  0.79645170
##  [4,] -0.28323215  0.5801748 -0.12332339
##  [5,] -0.04245237  0.6249194 -0.17739638
##  [6,]  0.73848529 -0.3565392  0.41421407
##  [7,]  0.25351696  0.0967388  0.07516695
##  [8,]  0.70535894 -0.0583019  0.63290657
##  [9,] -0.40904003  0.4258805  0.06960436
## [10,]  0.89193270  0.9614112  0.69245810
## [11,]  0.71226783  0.4273181  0.85853670
## [12,] -0.38177999  0.2820538  0.97603926
## 
## Effects documentation written to file C:/Users/sdr8y/OneDrive - University of Missouri/Research/Search_networks/SaoMNK/R/_rsiena_effects_doc_.html .
# ## Uncomment for HTML output with filterable data table
env1$preview_effects(structure_model, filter=TRUE)
## $effect
## [1] "XWX"
## 
## $parameter
## [1] 1
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$component_1_coDyadCovar"
## 
## $x
##       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
##  [1,]    1    1    1    0    0    0    0    0    0
##  [2,]    1    1    1    0    0    0    0    0    0
##  [3,]    1    1    1    0    0    0    0    0    0
##  [4,]    0    0    0    1    1    1    0    0    0
##  [5,]    0    0    0    1    1    1    0    0    0
##  [6,]    0    0    0    1    1    1    0    0    0
##  [7,]    0    0    0    0    0    0    1    1    1
##  [8,]    0    0    0    0    0    0    1    1    1
##  [9,]    0    0    0    0    0    0    1    1    1
## 
## $effect
## [1] "X"
## 
## $parameter
## [1] 0
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$component_2_coDyadCovar"
## 
## $x
##              [,1]         [,2]        [,3]        [,4]       [,5]         [,6]
##  [1,]  0.98460541 -0.009871387  0.52275043 -0.01816299 -0.3794959  0.919646128
##  [2,] -0.44819685  0.948122985  0.05515619 -0.40970726  0.1532957  0.532530035
##  [3,] -0.27143976  0.561222816  0.04243836 -0.43481532 -0.1451293  0.258300585
##  [4,]  0.60352743  0.466813955  0.80319235 -0.41741927  0.6873517  0.059404367
##  [5,] -0.49829512  0.084742727  0.85623200  0.43831420 -0.1119735  0.003707558
##  [6,]  0.08680500  0.547815459  0.42613685  0.94670543  0.9789757 -0.427622971
##  [7,]  0.19374198  0.316086797 -0.29895255  0.74095430  0.6353106  0.428421309
##  [8,]  0.08221597 -0.160299232  0.67328992 -0.02745765  0.9696674  0.942170938
##  [9,]  0.10372771  0.226836633  0.14379823 -0.18046182 -0.1715782  0.482440764
## [10,] -0.23155462  0.689510755  0.89091096  0.59874418  0.9230608  0.265437987
## [11,]  0.92748813 -0.491018556  0.65986484  0.24886153 -0.2758131 -0.274852684
## [12,]  0.18059211 -0.218431331 -0.11047813  0.59465796  0.4005355  0.805671821
##              [,7]       [,8]        [,9]
##  [1,]  0.27166252  0.4013924  0.85375569
##  [2,] -0.48702813  0.5721698  0.45618165
##  [3,] -0.47120785  0.2707685  0.79645170
##  [4,] -0.28323215  0.5801748 -0.12332339
##  [5,] -0.04245237  0.6249194 -0.17739638
##  [6,]  0.73848529 -0.3565392  0.41421407
##  [7,]  0.25351696  0.0967388  0.07516695
##  [8,]  0.70535894 -0.0583019  0.63290657
##  [9,] -0.40904003  0.4258805  0.06960436
## [10,]  0.89193270  0.9614112  0.69245810
## [11,]  0.71226783  0.4273181  0.85853670
## [12,] -0.38177999  0.2820538  0.97603926
## 
## Effects documentation written to file C:/Users/sdr8y/OneDrive - University of Missouri/Research/Search_networks/SaoMNK/R/_rsiena_effects_doc_.html .

1.3 Run RSiena Search Process

## TODO:  PICK UP WITH coDydCovar Interation Matrix

## Run Rsiena search using variable parameters in theta_matrix
env1$search_rsiena(
  structure_model,
  iterations = env1$M * steps_per_actor,
  digits = 4,
  run_seed = 12345
)
## $effect
## [1] "XWX"
## 
## $parameter
## [1] 1
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$component_1_coDyadCovar"
## 
## $x
##       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
##  [1,]    1    1    1    0    0    0    0    0    0
##  [2,]    1    1    1    0    0    0    0    0    0
##  [3,]    1    1    1    0    0    0    0    0    0
##  [4,]    0    0    0    1    1    1    0    0    0
##  [5,]    0    0    0    1    1    1    0    0    0
##  [6,]    0    0    0    1    1    1    0    0    0
##  [7,]    0    0    0    0    0    0    1    1    1
##  [8,]    0    0    0    0    0    0    1    1    1
##  [9,]    0    0    0    0    0    0    1    1    1
## 
## $effect
## [1] "X"
## 
## $parameter
## [1] 0
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$component_2_coDyadCovar"
## 
## $x
##              [,1]         [,2]        [,3]        [,4]       [,5]         [,6]
##  [1,]  0.98460541 -0.009871387  0.52275043 -0.01816299 -0.3794959  0.919646128
##  [2,] -0.44819685  0.948122985  0.05515619 -0.40970726  0.1532957  0.532530035
##  [3,] -0.27143976  0.561222816  0.04243836 -0.43481532 -0.1451293  0.258300585
##  [4,]  0.60352743  0.466813955  0.80319235 -0.41741927  0.6873517  0.059404367
##  [5,] -0.49829512  0.084742727  0.85623200  0.43831420 -0.1119735  0.003707558
##  [6,]  0.08680500  0.547815459  0.42613685  0.94670543  0.9789757 -0.427622971
##  [7,]  0.19374198  0.316086797 -0.29895255  0.74095430  0.6353106  0.428421309
##  [8,]  0.08221597 -0.160299232  0.67328992 -0.02745765  0.9696674  0.942170938
##  [9,]  0.10372771  0.226836633  0.14379823 -0.18046182 -0.1715782  0.482440764
## [10,] -0.23155462  0.689510755  0.89091096  0.59874418  0.9230608  0.265437987
## [11,]  0.92748813 -0.491018556  0.65986484  0.24886153 -0.2758131 -0.274852684
## [12,]  0.18059211 -0.218431331 -0.11047813  0.59465796  0.4005355  0.805671821
##              [,7]       [,8]        [,9]
##  [1,]  0.27166252  0.4013924  0.85375569
##  [2,] -0.48702813  0.5721698  0.45618165
##  [3,] -0.47120785  0.2707685  0.79645170
##  [4,] -0.28323215  0.5801748 -0.12332339
##  [5,] -0.04245237  0.6249194 -0.17739638
##  [6,]  0.73848529 -0.3565392  0.41421407
##  [7,]  0.25351696  0.0967388  0.07516695
##  [8,]  0.70535894 -0.0583019  0.63290657
##  [9,] -0.40904003  0.4258805  0.06960436
## [10,]  0.89193270  0.9614112  0.69245810
## [11,]  0.71226783  0.4273181  0.85853670
## [12,] -0.38177999  0.2820538  0.97603926
## 
## 
## 
## self$rsiena_data : 
## 
## Dependent variables:  self$bipartite_rsienaDV 
## Number of observations: 2 
## 
## Nodesets                 ACTORS      COMPONENTS 
## Number of nodes              12               9 
## 
## Dependent variable self$bipartite_rsienaDV
## Type               bipartite              
## Observations       2                      
## First nodeset      ACTORS                 
## Second nodeset     COMPONENTS             
## Densities          NA NA                  
## 
## Constant covariates:  self$strat_1_coCovar, self$strat_2_coCovar 
## Constant dyadic covariates:  self$component_1_coDyadCovar, self$component_2_coDyadCovar 
## 
##  structural effects i=1, j=1
## $effect
## [1] "density"
## 
## $parameter
## [1] 0
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
##   effectName          include fix  test  initialValue parm
## 1 outdegree (density) TRUE    TRUE FALSE   -1.60944   0   
##   effectName          include fix  test  initialValue parm
## 1 outdegree (density) TRUE    TRUE FALSE          0   0   
## 
##  structural effects i=1, j=2
## $effect
## [1] "inPop"
## 
## $parameter
## [1] 0
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
##   effectName            include fix  test  initialValue parm
## 1 indegree - popularity TRUE    TRUE FALSE          0   0   
##   effectName            include fix  test  initialValue parm
## 1 indegree - popularity TRUE    TRUE FALSE          0   0   
## 
##  structural effects i=1, j=3
## $effect
## [1] "outAct"
## 
## $parameter
## [1] 0
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
##   effectName           include fix  test  initialValue parm
## 1 outdegree - activity TRUE    TRUE FALSE          0   0   
##   effectName           include fix  test  initialValue parm
## 1 outdegree - activity TRUE    TRUE FALSE          0   0   
## 
##  coCovars i=1, j=1
## $effect
## [1] "egoX"
## 
## $parameter
## [1] 0
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$strat_1_coCovar"
## 
## $x
##  [1] -1  0  1 -1  0  1 -1  0  1 -1  0  1
## 
##   effectName               include fix  test  initialValue parm
## 1 self$strat_1_coCovar ego TRUE    TRUE FALSE          0   0   
##   effectName               include fix  test  initialValue parm
## 1 self$strat_1_coCovar ego TRUE    TRUE FALSE          0   0   
## 
##  coCovars i=1, j=2
## $effect
## [1] "inPopX"
## 
## $parameter
## [1] 0
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$strat_2_coCovar"
## 
## $x
##  [1]  1  0 -1  1  0 -1  1  0 -1  1  0 -1
## 
##   effectName                                    include fix  test  initialValue
## 1 ind. pop.^(1/#) weighted self$strat_2_coCovar TRUE    TRUE FALSE          0  
##   parm
## 1 1   
##   effectName                                    include fix  test  initialValue
## 1 ind. pop.^(1/#) weighted self$strat_2_coCovar TRUE    TRUE FALSE          0  
##   parm
## 1 0   
## 
##  coDyadCovars i=1, j=1
## $effect
## [1] "XWX"
## 
## $parameter
## [1] 1
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$component_1_coDyadCovar"
## 
## $x
##       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
##  [1,]    1    1    1    0    0    0    0    0    0
##  [2,]    1    1    1    0    0    0    0    0    0
##  [3,]    1    1    1    0    0    0    0    0    0
##  [4,]    0    0    0    1    1    1    0    0    0
##  [5,]    0    0    0    1    1    1    0    0    0
##  [6,]    0    0    0    1    1    1    0    0    0
##  [7,]    0    0    0    0    0    0    1    1    1
##  [8,]    0    0    0    0    0    0    1    1    1
##  [9,]    0    0    0    0    0    0    1    1    1
## 
##   effectName                                    include fix  test  initialValue
## 1 XW=>X closure of self$component_1_coDyadCovar TRUE    TRUE FALSE          0  
##   parm
## 1 0   
##   effectName                                    include fix  test  initialValue
## 1 XW=>X closure of self$component_1_coDyadCovar TRUE    TRUE FALSE          0  
##   parm
## 1 1   
## 
##  coDyadCovars i=1, j=2
## $effect
## [1] "X"
## 
## $parameter
## [1] 0
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$component_2_coDyadCovar"
## 
## $x
##              [,1]         [,2]        [,3]        [,4]       [,5]         [,6]
##  [1,]  0.98460541 -0.009871387  0.52275043 -0.01816299 -0.3794959  0.919646128
##  [2,] -0.44819685  0.948122985  0.05515619 -0.40970726  0.1532957  0.532530035
##  [3,] -0.27143976  0.561222816  0.04243836 -0.43481532 -0.1451293  0.258300585
##  [4,]  0.60352743  0.466813955  0.80319235 -0.41741927  0.6873517  0.059404367
##  [5,] -0.49829512  0.084742727  0.85623200  0.43831420 -0.1119735  0.003707558
##  [6,]  0.08680500  0.547815459  0.42613685  0.94670543  0.9789757 -0.427622971
##  [7,]  0.19374198  0.316086797 -0.29895255  0.74095430  0.6353106  0.428421309
##  [8,]  0.08221597 -0.160299232  0.67328992 -0.02745765  0.9696674  0.942170938
##  [9,]  0.10372771  0.226836633  0.14379823 -0.18046182 -0.1715782  0.482440764
## [10,] -0.23155462  0.689510755  0.89091096  0.59874418  0.9230608  0.265437987
## [11,]  0.92748813 -0.491018556  0.65986484  0.24886153 -0.2758131 -0.274852684
## [12,]  0.18059211 -0.218431331 -0.11047813  0.59465796  0.4005355  0.805671821
##              [,7]       [,8]        [,9]
##  [1,]  0.27166252  0.4013924  0.85375569
##  [2,] -0.48702813  0.5721698  0.45618165
##  [3,] -0.47120785  0.2707685  0.79645170
##  [4,] -0.28323215  0.5801748 -0.12332339
##  [5,] -0.04245237  0.6249194 -0.17739638
##  [6,]  0.73848529 -0.3565392  0.41421407
##  [7,]  0.25351696  0.0967388  0.07516695
##  [8,]  0.70535894 -0.0583019  0.63290657
##  [9,] -0.40904003  0.4258805  0.06960436
## [10,]  0.89193270  0.9614112  0.69245810
## [11,]  0.71226783  0.4273181  0.85853670
## [12,] -0.38177999  0.2820538  0.97603926
## 
## There is no effect with short name X, 
## and with interaction1 = <>, interaction2 = <>, and type = <eval>, 
## for dependent variable self$bipartite_rsienaDV .
## See effectsDocumentation() for this effects object.
##   effectName                   include fix  test  initialValue parm
## 1 self$component_2_coDyadCovar TRUE    TRUE FALSE          0   0   
## 
##  interactions i=1, j=1
## $effect
## [1] "egoX|XWX"
## 
## $parameter
## [1] 0
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$strat_1_coCovar"
## 
## $interaction2
## [1] "self$component_1_coDyadCovar"
## 
## $effects
## [1] "egoX" "XWX" 
## 
##   effectName                                                              
## 1 self$strat_1_coCovar ego x XW=>X closure of self$component_1_coDyadCovar
##   include fix  test  initialValue parm effect1 effect2
## 1 TRUE    TRUE FALSE          0   0    88      80     
## 
##  interactions i=1, j=2
## $effect
## [1] "inPopX|X"
## 
## $parameter
## [1] 0
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$strat_2_coCovar"
## 
## $interaction2
## [1] "self$component_2_coDyadCovar"
## 
## $effects
## [1] "inPopX" "X"     
## 
##   effectName                                                                  
## 1 ind. pop.^(1/0) weighted self$strat_2_coCovar x self$component_2_coDyadCovar
##   include fix  test  initialValue parm effect1 effect2
## 1 TRUE    TRUE FALSE          0   0    169     85     
## [1] "density"
## [1] "inPop"
## [1] "outAct"
## [1] "XWX"
## [1] "X"
## [1] "egoX"
## [1] "inPopX"
## [1] "egoX|XWX"
## [1] "inPopX|X"
## 
## 
##  theta_matrix : 
## 
##        density inPop outAct XWX X egoX inPopX egoX|XWX inPopX|X
##   [1,]       0     0      0   1 0    0      0        0        0
##   [2,]       0     0      0   1 0    0      0        0        0
##   [3,]       0     0      0   1 0    0      0        0        0
##   [4,]       0     0      0   1 0    0      0        0        0
##   [5,]       0     0      0   1 0    0      0        0        0
##   [6,]       0     0      0   1 0    0      0        0        0
##   [7,]       0     0      0   1 0    0      0        0        0
##   [8,]       0     0      0   1 0    0      0        0        0
##   [9,]       0     0      0   1 0    0      0        0        0
##  [10,]       0     0      0   1 0    0      0        0        0
##  [11,]       0     0      0   1 0    0      0        0        0
##  [12,]       0     0      0   1 0    0      0        0        0
##  [13,]       0     0      0   1 0    0      0        0        0
##  [14,]       0     0      0   1 0    0      0        0        0
##  [15,]       0     0      0   1 0    0      0        0        0
##  [16,]       0     0      0   1 0    0      0        0        0
##  [17,]       0     0      0   1 0    0      0        0        0
##  [18,]       0     0      0   1 0    0      0        0        0
##  [19,]       0     0      0   1 0    0      0        0        0
##  [20,]       0     0      0   1 0    0      0        0        0
##  [21,]       0     0      0   1 0    0      0        0        0
##  [22,]       0     0      0   1 0    0      0        0        0
##  [23,]       0     0      0   1 0    0      0        0        0
##  [24,]       0     0      0   1 0    0      0        0        0
##  [25,]       0     0      0   1 0    0      0        0        0
##  [26,]       0     0      0   1 0    0      0        0        0
##  [27,]       0     0      0   1 0    0      0        0        0
##  [28,]       0     0      0   1 0    0      0        0        0
##  [29,]       0     0      0   1 0    0      0        0        0
##  [30,]       0     0      0   1 0    0      0        0        0
##  [31,]       0     0      0   1 0    0      0        0        0
##  [32,]       0     0      0   1 0    0      0        0        0
##  [33,]       0     0      0   1 0    0      0        0        0
##  [34,]       0     0      0   1 0    0      0        0        0
##  [35,]       0     0      0   1 0    0      0        0        0
##  [36,]       0     0      0   1 0    0      0        0        0
##  [37,]       0     0      0   1 0    0      0        0        0
##  [38,]       0     0      0   1 0    0      0        0        0
##  [39,]       0     0      0   1 0    0      0        0        0
##  [40,]       0     0      0   1 0    0      0        0        0
##  [41,]       0     0      0   1 0    0      0        0        0
##  [42,]       0     0      0   1 0    0      0        0        0
##  [43,]       0     0      0   1 0    0      0        0        0
##  [44,]       0     0      0   1 0    0      0        0        0
##  [45,]       0     0      0   1 0    0      0        0        0
##  [46,]       0     0      0   1 0    0      0        0        0
##  [47,]       0     0      0   1 0    0      0        0        0
##  [48,]       0     0      0   1 0    0      0        0        0
##  [49,]       0     0      0   1 0    0      0        0        0
##  [50,]       0     0      0   1 0    0      0        0        0
##  [51,]       0     0      0   1 0    0      0        0        0
##  [52,]       0     0      0   1 0    0      0        0        0
##  [53,]       0     0      0   1 0    0      0        0        0
##  [54,]       0     0      0   1 0    0      0        0        0
##  [55,]       0     0      0   1 0    0      0        0        0
##  [56,]       0     0      0   1 0    0      0        0        0
##  [57,]       0     0      0   1 0    0      0        0        0
##  [58,]       0     0      0   1 0    0      0        0        0
##  [59,]       0     0      0   1 0    0      0        0        0
##  [60,]       0     0      0   1 0    0      0        0        0
##  [61,]       0     0      0   1 0    0      0        0        0
##  [62,]       0     0      0   1 0    0      0        0        0
##  [63,]       0     0      0   1 0    0      0        0        0
##  [64,]       0     0      0   1 0    0      0        0        0
##  [65,]       0     0      0   1 0    0      0        0        0
##  [66,]       0     0      0   1 0    0      0        0        0
##  [67,]       0     0      0   1 0    0      0        0        0
##  [68,]       0     0      0   1 0    0      0        0        0
##  [69,]       0     0      0   1 0    0      0        0        0
##  [70,]       0     0      0   1 0    0      0        0        0
##  [71,]       0     0      0   1 0    0      0        0        0
##  [72,]       0     0      0   1 0    0      0        0        0
##  [73,]       0     0      0   1 0    0      0        0        0
##  [74,]       0     0      0   1 0    0      0        0        0
##  [75,]       0     0      0   1 0    0      0        0        0
##  [76,]       0     0      0   1 0    0      0        0        0
##  [77,]       0     0      0   1 0    0      0        0        0
##  [78,]       0     0      0   1 0    0      0        0        0
##  [79,]       0     0      0   1 0    0      0        0        0
##  [80,]       0     0      0   1 0    0      0        0        0
##  [81,]       0     0      0   1 0    0      0        0        0
##  [82,]       0     0      0   1 0    0      0        0        0
##  [83,]       0     0      0   1 0    0      0        0        0
##  [84,]       0     0      0   1 0    0      0        0        0
##  [85,]       0     0      0   1 0    0      0        0        0
##  [86,]       0     0      0   1 0    0      0        0        0
##  [87,]       0     0      0   1 0    0      0        0        0
##  [88,]       0     0      0   1 0    0      0        0        0
##  [89,]       0     0      0   1 0    0      0        0        0
##  [90,]       0     0      0   1 0    0      0        0        0
##  [91,]       0     0      0   1 0    0      0        0        0
##  [92,]       0     0      0   1 0    0      0        0        0
##  [93,]       0     0      0   1 0    0      0        0        0
##  [94,]       0     0      0   1 0    0      0        0        0
##  [95,]       0     0      0   1 0    0      0        0        0
##  [96,]       0     0      0   1 0    0      0        0        0
##  [97,]       0     0      0   1 0    0      0        0        0
##  [98,]       0     0      0   1 0    0      0        0        0
##  [99,]       0     0      0   1 0    0      0        0        0
## [100,]       0     0      0   1 0    0      0        0        0
## [101,]       0     0      0   1 0    0      0        0        0
## [102,]       0     0      0   1 0    0      0        0        0
## [103,]       0     0      0   1 0    0      0        0        0
## [104,]       0     0      0   1 0    0      0        0        0
## [105,]       0     0      0   1 0    0      0        0        0
## [106,]       0     0      0   1 0    0      0        0        0
## [107,]       0     0      0   1 0    0      0        0        0
## [108,]       0     0      0   1 0    0      0        0        0
## [109,]       0     0      0   1 0    0      0        0        0
## [110,]       0     0      0   1 0    0      0        0        0
## [111,]       0     0      0   1 0    0      0        0        0
## [112,]       0     0      0   1 0    0      0        0        0
## [113,]       0     0      0   1 0    0      0        0        0
## [114,]       0     0      0   1 0    0      0        0        0
## [115,]       0     0      0   1 0    0      0        0        0
## [116,]       0     0      0   1 0    0      0        0        0
## [117,]       0     0      0   1 0    0      0        0        0
## [118,]       0     0      0   1 0    0      0        0        0
## [119,]       0     0      0   1 0    0      0        0        0
## [120,]       0     0      0   1 0    0      0        0        0
## [121,]       0     0      0   1 0    0      0        0        0
## [122,]       0     0      0   1 0    0      0        0        0
## [123,]       0     0      0   1 0    0      0        0        0
## [124,]       0     0      0   1 0    0      0        0        0
## [125,]       0     0      0   1 0    0      0        0        0
## [126,]       0     0      0   1 0    0      0        0        0
## [127,]       0     0      0   1 0    0      0        0        0
## [128,]       0     0      0   1 0    0      0        0        0
## [129,]       0     0      0   1 0    0      0        0        0
## [130,]       0     0      0   1 0    0      0        0        0
## [131,]       0     0      0   1 0    0      0        0        0
## [132,]       0     0      0   1 0    0      0        0        0
## [133,]       0     0      0   1 0    0      0        0        0
## [134,]       0     0      0   1 0    0      0        0        0
## [135,]       0     0      0   1 0    0      0        0        0
## [136,]       0     0      0   1 0    0      0        0        0
## [137,]       0     0      0   1 0    0      0        0        0
## [138,]       0     0      0   1 0    0      0        0        0
## [139,]       0     0      0   1 0    0      0        0        0
## [140,]       0     0      0   1 0    0      0        0        0
## [141,]       0     0      0   1 0    0      0        0        0
## [142,]       0     0      0   1 0    0      0        0        0
## [143,]       0     0      0   1 0    0      0        0        0
## [144,]       0     0      0   1 0    0      0        0        0
## [145,]       0     0      0   1 0    0      0        0        0
## [146,]       0     0      0   1 0    0      0        0        0
## [147,]       0     0      0   1 0    0      0        0        0
## [148,]       0     0      0   1 0    0      0        0        0
## [149,]       0     0      0   1 0    0      0        0        0
## [150,]       0     0      0   1 0    0      0        0        0
## [151,]       0     0      0   1 0    0      0        0        0
## [152,]       0     0      0   1 0    0      0        0        0
## [153,]       0     0      0   1 0    0      0        0        0
## [154,]       0     0      0   1 0    0      0        0        0
## [155,]       0     0      0   1 0    0      0        0        0
## [156,]       0     0      0   1 0    0      0        0        0
## [157,]       0     0      0   1 0    0      0        0        0
## [158,]       0     0      0   1 0    0      0        0        0
## [159,]       0     0      0   1 0    0      0        0        0
## [160,]       0     0      0   1 0    0      0        0        0
## [161,]       0     0      0   1 0    0      0        0        0
## [162,]       0     0      0   1 0    0      0        0        0
## [163,]       0     0      0   1 0    0      0        0        0
## [164,]       0     0      0   1 0    0      0        0        0
## [165,]       0     0      0   1 0    0      0        0        0
## [166,]       0     0      0   1 0    0      0        0        0
## [167,]       0     0      0   1 0    0      0        0        0
## [168,]       0     0      0   1 0    0      0        0        0
## [169,]       0     0      0   1 0    0      0        0        0
## [170,]       0     0      0   1 0    0      0        0        0
## [171,]       0     0      0   1 0    0      0        0        0
## [172,]       0     0      0   1 0    0      0        0        0
## [173,]       0     0      0   1 0    0      0        0        0
## [174,]       0     0      0   1 0    0      0        0        0
## [175,]       0     0      0   1 0    0      0        0        0
## [176,]       0     0      0   1 0    0      0        0        0
## [177,]       0     0      0   1 0    0      0        0        0
## [178,]       0     0      0   1 0    0      0        0        0
## [179,]       0     0      0   1 0    0      0        0        0
## [180,]       0     0      0   1 0    0      0        0        0
## [181,]       0     0      0   1 0    0      0        0        0
## [182,]       0     0      0   1 0    0      0        0        0
## [183,]       0     0      0   1 0    0      0        0        0
## [184,]       0     0      0   1 0    0      0        0        0
## [185,]       0     0      0   1 0    0      0        0        0
## [186,]       0     0      0   1 0    0      0        0        0
## [187,]       0     0      0   1 0    0      0        0        0
## [188,]       0     0      0   1 0    0      0        0        0
## [189,]       0     0      0   1 0    0      0        0        0
## [190,]       0     0      0   1 0    0      0        0        0
## [191,]       0     0      0   1 0    0      0        0        0
## [192,]       0     0      0   1 0    0      0        0        0
## [193,]       0     0      0   1 0    0      0        0        0
## [194,]       0     0      0   1 0    0      0        0        0
## [195,]       0     0      0   1 0    0      0        0        0
## [196,]       0     0      0   1 0    0      0        0        0
## [197,]       0     0      0   1 0    0      0        0        0
## [198,]       0     0      0   1 0    0      0        0        0
## [199,]       0     0      0   1 0    0      0        0        0
## [200,]       0     0      0   1 0    0      0        0        0
## [201,]       0     0      0   1 0    0      0        0        0
## [202,]       0     0      0   1 0    0      0        0        0
## [203,]       0     0      0   1 0    0      0        0        0
## [204,]       0     0      0   1 0    0      0        0        0
## [205,]       0     0      0   1 0    0      0        0        0
## [206,]       0     0      0   1 0    0      0        0        0
## [207,]       0     0      0   1 0    0      0        0        0
## [208,]       0     0      0   1 0    0      0        0        0
## [209,]       0     0      0   1 0    0      0        0        0
## [210,]       0     0      0   1 0    0      0        0        0
## [211,]       0     0      0   1 0    0      0        0        0
## [212,]       0     0      0   1 0    0      0        0        0
## [213,]       0     0      0   1 0    0      0        0        0
## [214,]       0     0      0   1 0    0      0        0        0
## [215,]       0     0      0   1 0    0      0        0        0
## [216,]       0     0      0   1 0    0      0        0        0
## [217,]       0     0      0   1 0    0      0        0        0
## [218,]       0     0      0   1 0    0      0        0        0
## [219,]       0     0      0   1 0    0      0        0        0
## [220,]       0     0      0   1 0    0      0        0        0
## [221,]       0     0      0   1 0    0      0        0        0
## [222,]       0     0      0   1 0    0      0        0        0
## [223,]       0     0      0   1 0    0      0        0        0
## [224,]       0     0      0   1 0    0      0        0        0
## [225,]       0     0      0   1 0    0      0        0        0
## [226,]       0     0      0   1 0    0      0        0        0
## [227,]       0     0      0   1 0    0      0        0        0
## [228,]       0     0      0   1 0    0      0        0        0
## [229,]       0     0      0   1 0    0      0        0        0
## [230,]       0     0      0   1 0    0      0        0        0
## [231,]       0     0      0   1 0    0      0        0        0
## [232,]       0     0      0   1 0    0      0        0        0
## [233,]       0     0      0   1 0    0      0        0        0
## [234,]       0     0      0   1 0    0      0        0        0
## [235,]       0     0      0   1 0    0      0        0        0
## [236,]       0     0      0   1 0    0      0        0        0
## [237,]       0     0      0   1 0    0      0        0        0
## [238,]       0     0      0   1 0    0      0        0        0
## [239,]       0     0      0   1 0    0      0        0        0
## [240,]       0     0      0   1 0    0      0        0        0
## [241,]       0     0      0   1 0    0      0        0        0
## [242,]       0     0      0   1 0    0      0        0        0
## [243,]       0     0      0   1 0    0      0        0        0
## [244,]       0     0      0   1 0    0      0        0        0
## [245,]       0     0      0   1 0    0      0        0        0
## [246,]       0     0      0   1 0    0      0        0        0
## [247,]       0     0      0   1 0    0      0        0        0
## [248,]       0     0      0   1 0    0      0        0        0
## [249,]       0     0      0   1 0    0      0        0        0
## [250,]       0     0      0   1 0    0      0        0        0
## [251,]       0     0      0   1 0    0      0        0        0
## [252,]       0     0      0   1 0    0      0        0        0
## [253,]       0     0      0   1 0    0      0        0        0
## [254,]       0     0      0   1 0    0      0        0        0
## [255,]       0     0      0   1 0    0      0        0        0
## [256,]       0     0      0   1 0    0      0        0        0
## [257,]       0     0      0   1 0    0      0        0        0
## [258,]       0     0      0   1 0    0      0        0        0
## [259,]       0     0      0   1 0    0      0        0        0
## [260,]       0     0      0   1 0    0      0        0        0
## [261,]       0     0      0   1 0    0      0        0        0
## [262,]       0     0      0   1 0    0      0        0        0
## [263,]       0     0      0   1 0    0      0        0        0
## [264,]       0     0      0   1 0    0      0        0        0
## [265,]       0     0      0   1 0    0      0        0        0
## [266,]       0     0      0   1 0    0      0        0        0
## [267,]       0     0      0   1 0    0      0        0        0
## [268,]       0     0      0   1 0    0      0        0        0
## [269,]       0     0      0   1 0    0      0        0        0
## [270,]       0     0      0   1 0    0      0        0        0
## [271,]       0     0      0   1 0    0      0        0        0
## [272,]       0     0      0   1 0    0      0        0        0
## [273,]       0     0      0   1 0    0      0        0        0
## [274,]       0     0      0   1 0    0      0        0        0
## [275,]       0     0      0   1 0    0      0        0        0
## [276,]       0     0      0   1 0    0      0        0        0
## [277,]       0     0      0   1 0    0      0        0        0
## [278,]       0     0      0   1 0    0      0        0        0
## [279,]       0     0      0   1 0    0      0        0        0
## [280,]       0     0      0   1 0    0      0        0        0
## [281,]       0     0      0   1 0    0      0        0        0
## [282,]       0     0      0   1 0    0      0        0        0
## [283,]       0     0      0   1 0    0      0        0        0
## [284,]       0     0      0   1 0    0      0        0        0
## [285,]       0     0      0   1 0    0      0        0        0
## [286,]       0     0      0   1 0    0      0        0        0
## [287,]       0     0      0   1 0    0      0        0        0
## [288,]       0     0      0   1 0    0      0        0        0
## [289,]       0     0      0   1 0    0      0        0        0
## [290,]       0     0      0   1 0    0      0        0        0
## [291,]       0     0      0   1 0    0      0        0        0
## [292,]       0     0      0   1 0    0      0        0        0
## [293,]       0     0      0   1 0    0      0        0        0
## [294,]       0     0      0   1 0    0      0        0        0
## [295,]       0     0      0   1 0    0      0        0        0
## [296,]       0     0      0   1 0    0      0        0        0
## [297,]       0     0      0   1 0    0      0        0        0
## [298,]       0     0      0   1 0    0      0        0        0
## [299,]       0     0      0   1 0    0      0        0        0
## [300,]       0     0      0   1 0    0      0        0        0
## If you use this algorithm object, siena07 will create/use an output file C:/Users/sdr8y/OneDrive - University of Missouri/Research/Search_networks/SaoMNK/R/_test_tutorial_nb__173926268866.txt .
## 
## Start phase 0 
## theta: 0 0 0 0 0 0 0 0 0 
## 
## Start phase 3 
## Phase 3 Iteration 100 Progress 33%
## Phase 3 Iteration 200 Progress 67%
## Phase 3 Iteration 300 Progress 100%
## Parameter values used for simulations
## 
##                                                                                        Mean      Standard      
##                                                                                          value   Deviation     
## 
## Rate parameters: 
##   0       Rate parameter                                                               NA      ( NA        )   
## 
## Other parameters: 
##   1. eval outdegree (density)                                                           0      ( NA        )   
##   2. eval indegree - popularity                                                         0      ( NA        )   
##   3. eval outdegree - activity                                                          0      ( NA        )   
##   4. eval XW=>X closure of self$component_1_coDyadCovar                                 1      ( NA        )   
##   5. eval self$component_2_coDyadCovar                                                  0      ( NA        )   
##   6. eval self$strat_1_coCovar ego                                                      0      ( NA        )   
##   7. eval ind. pop.^(1/0) weighted self$strat_2_coCovar                                 0      ( NA        )   
##   8. eval self$strat_1_coCovar ego x XW=>X closure of self$component_1_coDyadCovar      0      ( NA        )   
##   9. eval ind. pop.^(1/0) weighted self$strat_2_coCovar x self$component_2_coDyadCovar  0      ( NA        )   
## 
## Simulated means and standard deviations
##   1. Number of ties                                                                 0.867    0.341 
##   2. Sum of squared indegrees                                                       0.867    0.341 
##   3. Sum of squared outdegrees                                                      0.867    0.341 
##   4. XW=>X closure of self$component_1_coDyadCovar                                  0.000    0.000 
##   5. Sum of ties x self$component_2_coDyadCovar                                    -0.037    0.418 
##   6. Sum of outdegrees x self$strat_1_coCovar                                      -0.063    0.758 
##   7. indegree pop.^(1/0) weighted self$strat_2_coCovar                              0.063    0.758 
##   8. self$strat_1_coCovar ego x XW=>X closure of self$component_1_coDyadCovar       0.000    0.000 
##   9. ind. pop.^(1/0) weighted self$strat_2_coCovar x self$component_2_coDyadCovar   0.071    0.316 
## 
## 
## Simulated statistics are in x$sf
## and simulated dependent variables in x$sims, where x is the created object.
## 
## Total of 300 iteration steps.
## 
## Covariance matrix of estimates (correlations below diagonal)
## 
##            0            0            0            0            0            0            0            0            0
##          NaN            0            0            0            0            0            0            0            0
##          NaN          NaN            0            0            0            0            0            0            0
##          NaN          NaN          NaN            0            0            0            0            0            0
##          NaN          NaN          NaN          NaN            0            0            0            0            0
##          NaN          NaN          NaN          NaN          NaN            0            0            0            0
##          NaN          NaN          NaN          NaN          NaN          NaN            0            0            0
##          NaN          NaN          NaN          NaN          NaN          NaN          NaN            0            0
##          NaN          NaN          NaN          NaN          NaN          NaN          NaN          NaN            0
## 
## Derivative matrix of expected statistics X by parameters:
## 
##        0.116        0.116        0.116        0.000       -0.005       -0.008        0.008        0.000        0.010
##        0.116        0.116        0.116        0.000       -0.005       -0.008        0.008        0.000        0.010
##        0.116        0.116        0.116        0.000       -0.005       -0.008        0.008        0.000        0.010
##        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000
##       -0.005       -0.005       -0.005        0.000        0.152       -0.018        0.018        0.000        0.008
##        0.007        0.007        0.007        0.000       -0.008        0.057       -0.057        0.000        0.003
##        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000
##        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000
##        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000
## 
## Covariance matrix of X (correlations below diagonal):
## 
##        0.116        0.116        0.116        0.000       -0.005       -0.008        0.008        0.000        0.010
##        1.000        0.116        0.116        0.000       -0.005       -0.008        0.008        0.000        0.010
##        1.000        1.000        0.116        0.000       -0.005       -0.008        0.008        0.000        0.010
##          NaN          NaN          NaN        0.000        0.000        0.000        0.000        0.000        0.000
##       -0.035       -0.035       -0.035          NaN        0.175       -0.074        0.074        0.000        0.008
##       -0.033       -0.033       -0.033          NaN       -0.233        0.575       -0.575        0.000        0.029
##        0.033        0.033        0.033          NaN        0.233       -1.000        0.575        0.000       -0.029
##          NaN          NaN          NaN          NaN          NaN          NaN          NaN        0.000        0.000
##        0.089        0.089        0.089          NaN        0.059        0.119       -0.119          NaN        0.100
## 
## 
## 
## Simulated Decision Chain Summary:
## 
##    dv_type           dv_type_bin  dv_varname           id_from      
##  Length:300         Min.   :0    Length:300         Min.   : 1.000  
##  Class :character   1st Qu.:0    Class :character   1st Qu.: 4.000  
##  Mode  :character   Median :0    Mode  :character   Median : 7.000  
##                     Mean   :0                       Mean   : 6.757  
##                     3rd Qu.:0                       3rd Qu.:10.000  
##                     Max.   :0                       Max.   :12.000  
##      id_to      beh_difference reciprocal_rate   LogOptionSetProb
##  Min.   : 1.0   Min.   :0      Min.   :0.08333   Min.   :-2.485  
##  1st Qu.: 3.0   1st Qu.:0      1st Qu.:0.08333   1st Qu.:-2.485  
##  Median : 6.0   Median :0      Median :0.08333   Median :-2.485  
##  Mean   : 5.6   Mean   :0      Mean   :0.08333   Mean   :-2.485  
##  3rd Qu.: 8.0   3rd Qu.:0      3rd Qu.:0.08333   3rd Qu.:-2.485  
##  Max.   :10.0   Max.   :0      Max.   :0.08333   Max.   :-2.485  
##  LogChoiceProb      diagonal         stability       tie_change     
##  Min.   :-2.303   Length:300         Mode :logical   Mode :logical  
##  1st Qu.:-2.303   Class :character   FALSE:260       FALSE:40       
##  Median :-2.303   Mode  :character   TRUE :40        TRUE :260      
##  Mean   :-2.303                                                     
##  3rd Qu.:-2.303                                                     
##  Max.   :-2.303                                                     
##  chain_step_id   
##  Min.   :  1.00  
##  1st Qu.: 75.75  
##  Median :150.50  
##  Mean   :150.34  
##  3rd Qu.:225.25  
##  Max.   :300.00  
## [1] 300  13
##     dv_type dv_type_bin              dv_varname id_from id_to beh_difference
## 1   Network           0 self$bipartite_rsienaDV      11     8              0
## 2   Network           0 self$bipartite_rsienaDV       4     6              0
## 3   Network           0 self$bipartite_rsienaDV      12     1              0
## 4   Network           0 self$bipartite_rsienaDV       9     1              0
## 5   Network           0 self$bipartite_rsienaDV       6     4              0
## 6   Network           0 self$bipartite_rsienaDV       3    10              0
## 7   Network           0 self$bipartite_rsienaDV       9     7              0
## 8   Network           0 self$bipartite_rsienaDV       9     6              0
## 9   Network           0 self$bipartite_rsienaDV       1     2              0
## 10  Network           0 self$bipartite_rsienaDV       5     4              0
## 11  Network           0 self$bipartite_rsienaDV       2     8              0
## 12  Network           0 self$bipartite_rsienaDV       4     4              0
## 13  Network           0 self$bipartite_rsienaDV       8    10              0
## 14  Network           0 self$bipartite_rsienaDV       4     3              0
## 15  Network           0 self$bipartite_rsienaDV       6     8              0
## 16  Network           0 self$bipartite_rsienaDV       6     3              0
## 17  Network           0 self$bipartite_rsienaDV       4    10              0
## 18  Network           0 self$bipartite_rsienaDV      12     3              0
## 19  Network           0 self$bipartite_rsienaDV      12     7              0
## 20  Network           0 self$bipartite_rsienaDV       5     4              0
## 21  Network           0 self$bipartite_rsienaDV       8    10              0
## 22  Network           0 self$bipartite_rsienaDV       7     2              0
## 23  Network           0 self$bipartite_rsienaDV       1     2              0
## 24  Network           0 self$bipartite_rsienaDV      10     6              0
## 25  Network           0 self$bipartite_rsienaDV       1    10              0
## 26  Network           0 self$bipartite_rsienaDV       1     7              0
## 27  Network           0 self$bipartite_rsienaDV       7     8              0
## 28  Network           0 self$bipartite_rsienaDV       2     4              0
## 29  Network           0 self$bipartite_rsienaDV       8    10              0
## 30  Network           0 self$bipartite_rsienaDV       7    10              0
## 31  Network           0 self$bipartite_rsienaDV      11     3              0
## 32  Network           0 self$bipartite_rsienaDV      10     4              0
## 33  Network           0 self$bipartite_rsienaDV      11    10              0
## 34  Network           0 self$bipartite_rsienaDV       1     4              0
## 35  Network           0 self$bipartite_rsienaDV       7     1              0
## 36  Network           0 self$bipartite_rsienaDV       9     9              0
## 37  Network           0 self$bipartite_rsienaDV      10     1              0
## 38  Network           0 self$bipartite_rsienaDV      10     7              0
## 39  Network           0 self$bipartite_rsienaDV       3     1              0
## 40  Network           0 self$bipartite_rsienaDV       7     7              0
## 41  Network           0 self$bipartite_rsienaDV      12    10              0
## 42  Network           0 self$bipartite_rsienaDV       7     8              0
## 43  Network           0 self$bipartite_rsienaDV       3     8              0
## 44  Network           0 self$bipartite_rsienaDV       6     9              0
## 45  Network           0 self$bipartite_rsienaDV       9     6              0
## 46  Network           0 self$bipartite_rsienaDV       6    10              0
## 47  Network           0 self$bipartite_rsienaDV      11     4              0
## 48  Network           0 self$bipartite_rsienaDV       5     8              0
## 49  Network           0 self$bipartite_rsienaDV      12     8              0
## 50  Network           0 self$bipartite_rsienaDV       3     5              0
## 51  Network           0 self$bipartite_rsienaDV       4    10              0
## 52  Network           0 self$bipartite_rsienaDV       5    10              0
## 53  Network           0 self$bipartite_rsienaDV       2     8              0
## 54  Network           0 self$bipartite_rsienaDV      12     1              0
## 55  Network           0 self$bipartite_rsienaDV      10     3              0
## 56  Network           0 self$bipartite_rsienaDV       2     6              0
## 57  Network           0 self$bipartite_rsienaDV      10     1              0
## 58  Network           0 self$bipartite_rsienaDV       7     7              0
## 59  Network           0 self$bipartite_rsienaDV       9     4              0
## 60  Network           0 self$bipartite_rsienaDV      12     5              0
## 61  Network           0 self$bipartite_rsienaDV       7     7              0
## 62  Network           0 self$bipartite_rsienaDV       2     2              0
## 63  Network           0 self$bipartite_rsienaDV       7     9              0
## 64  Network           0 self$bipartite_rsienaDV      11     5              0
## 65  Network           0 self$bipartite_rsienaDV       7     5              0
## 66  Network           0 self$bipartite_rsienaDV       9     6              0
## 67  Network           0 self$bipartite_rsienaDV      12    10              0
## 68  Network           0 self$bipartite_rsienaDV       9    10              0
## 69  Network           0 self$bipartite_rsienaDV       5     8              0
## 70  Network           0 self$bipartite_rsienaDV      11     9              0
## 71  Network           0 self$bipartite_rsienaDV       3     2              0
## 72  Network           0 self$bipartite_rsienaDV      10    10              0
## 73  Network           0 self$bipartite_rsienaDV       1     2              0
## 74  Network           0 self$bipartite_rsienaDV      12     7              0
## 75  Network           0 self$bipartite_rsienaDV       4     2              0
## 76  Network           0 self$bipartite_rsienaDV       5     9              0
## 77  Network           0 self$bipartite_rsienaDV      10     1              0
## 78  Network           0 self$bipartite_rsienaDV       4     5              0
## 79  Network           0 self$bipartite_rsienaDV      10     6              0
## 80  Network           0 self$bipartite_rsienaDV       9     9              0
## 81  Network           0 self$bipartite_rsienaDV      10     3              0
## 82  Network           0 self$bipartite_rsienaDV       1     1              0
## 83  Network           0 self$bipartite_rsienaDV       9     7              0
## 84  Network           0 self$bipartite_rsienaDV       9     3              0
## 85  Network           0 self$bipartite_rsienaDV       5     5              0
## 86  Network           0 self$bipartite_rsienaDV      11     6              0
## 87  Network           0 self$bipartite_rsienaDV       4     9              0
## 88  Network           0 self$bipartite_rsienaDV       9     7              0
## 89  Network           0 self$bipartite_rsienaDV       5    10              0
## 90  Network           0 self$bipartite_rsienaDV       1     2              0
## 91  Network           0 self$bipartite_rsienaDV       9     7              0
## 92  Network           0 self$bipartite_rsienaDV       9     5              0
## 93  Network           0 self$bipartite_rsienaDV      11     9              0
## 94  Network           0 self$bipartite_rsienaDV       8     8              0
## 95  Network           0 self$bipartite_rsienaDV       9     7              0
## 96  Network           0 self$bipartite_rsienaDV       8     6              0
## 97  Network           0 self$bipartite_rsienaDV      10     2              0
## 98  Network           0 self$bipartite_rsienaDV       6     3              0
## 99  Network           0 self$bipartite_rsienaDV       9     9              0
## 100 Network           0 self$bipartite_rsienaDV      10     6              0
## 101 Network           0 self$bipartite_rsienaDV      10    10              0
## 102 Network           0 self$bipartite_rsienaDV       8     5              0
## 103 Network           0 self$bipartite_rsienaDV       6     8              0
## 104 Network           0 self$bipartite_rsienaDV       4     7              0
## 105 Network           0 self$bipartite_rsienaDV      11     7              0
## 106 Network           0 self$bipartite_rsienaDV      11     1              0
## 107 Network           0 self$bipartite_rsienaDV      11     9              0
## 108 Network           0 self$bipartite_rsienaDV       4     2              0
## 109 Network           0 self$bipartite_rsienaDV       5     6              0
## 110 Network           0 self$bipartite_rsienaDV       1     5              0
## 111 Network           0 self$bipartite_rsienaDV       3     6              0
## 112 Network           0 self$bipartite_rsienaDV      11     3              0
## 113 Network           0 self$bipartite_rsienaDV       1     6              0
## 114 Network           0 self$bipartite_rsienaDV       1     1              0
## 115 Network           0 self$bipartite_rsienaDV      10     6              0
## 116 Network           0 self$bipartite_rsienaDV       6     2              0
## 117 Network           0 self$bipartite_rsienaDV       4     2              0
## 118 Network           0 self$bipartite_rsienaDV       5     9              0
## 119 Network           0 self$bipartite_rsienaDV       8     1              0
## 120 Network           0 self$bipartite_rsienaDV       4     1              0
## 121 Network           0 self$bipartite_rsienaDV       1     9              0
## 122 Network           0 self$bipartite_rsienaDV       2     9              0
## 123 Network           0 self$bipartite_rsienaDV       1     7              0
## 124 Network           0 self$bipartite_rsienaDV       1    10              0
## 125 Network           0 self$bipartite_rsienaDV      10     6              0
## 126 Network           0 self$bipartite_rsienaDV      12     3              0
## 127 Network           0 self$bipartite_rsienaDV       2     6              0
## 128 Network           0 self$bipartite_rsienaDV       7     4              0
## 129 Network           0 self$bipartite_rsienaDV       5     9              0
## 130 Network           0 self$bipartite_rsienaDV       4     5              0
## 131 Network           0 self$bipartite_rsienaDV       8     3              0
## 132 Network           0 self$bipartite_rsienaDV       9     8              0
## 133 Network           0 self$bipartite_rsienaDV       2     3              0
## 134 Network           0 self$bipartite_rsienaDV       4     6              0
## 135 Network           0 self$bipartite_rsienaDV       8     2              0
## 136 Network           0 self$bipartite_rsienaDV      10     9              0
## 137 Network           0 self$bipartite_rsienaDV      10     8              0
## 138 Network           0 self$bipartite_rsienaDV      11    10              0
## 139 Network           0 self$bipartite_rsienaDV      11     1              0
## 140 Network           0 self$bipartite_rsienaDV       5     8              0
## 141 Network           0 self$bipartite_rsienaDV       5     4              0
## 142 Network           0 self$bipartite_rsienaDV       4     7              0
## 143 Network           0 self$bipartite_rsienaDV      10     8              0
## 144 Network           0 self$bipartite_rsienaDV      11     6              0
## 145 Network           0 self$bipartite_rsienaDV       7    10              0
## 146 Network           0 self$bipartite_rsienaDV       6     4              0
## 147 Network           0 self$bipartite_rsienaDV       8     7              0
## 148 Network           0 self$bipartite_rsienaDV       2    10              0
## 149 Network           0 self$bipartite_rsienaDV       5     3              0
## 150 Network           0 self$bipartite_rsienaDV       3     6              0
## 151 Network           0 self$bipartite_rsienaDV       7     1              0
## 152 Network           0 self$bipartite_rsienaDV       8     8              0
## 153 Network           0 self$bipartite_rsienaDV      11     4              0
## 154 Network           0 self$bipartite_rsienaDV       3     1              0
## 155 Network           0 self$bipartite_rsienaDV       5     1              0
## 156 Network           0 self$bipartite_rsienaDV       7     7              0
## 157 Network           0 self$bipartite_rsienaDV       4    10              0
## 158 Network           0 self$bipartite_rsienaDV       9     3              0
## 159 Network           0 self$bipartite_rsienaDV       8     6              0
## 160 Network           0 self$bipartite_rsienaDV      11     3              0
## 161 Network           0 self$bipartite_rsienaDV       7     4              0
## 162 Network           0 self$bipartite_rsienaDV       3     4              0
## 163 Network           0 self$bipartite_rsienaDV       9     2              0
## 164 Network           0 self$bipartite_rsienaDV       7     2              0
## 165 Network           0 self$bipartite_rsienaDV      10     3              0
## 166 Network           0 self$bipartite_rsienaDV       3    10              0
## 167 Network           0 self$bipartite_rsienaDV      10     7              0
## 168 Network           0 self$bipartite_rsienaDV       7     8              0
## 169 Network           0 self$bipartite_rsienaDV      10     9              0
## 170 Network           0 self$bipartite_rsienaDV       7     2              0
## 171 Network           0 self$bipartite_rsienaDV       1     4              0
## 172 Network           0 self$bipartite_rsienaDV      12     3              0
## 173 Network           0 self$bipartite_rsienaDV      11     5              0
## 174 Network           0 self$bipartite_rsienaDV      12     6              0
## 175 Network           0 self$bipartite_rsienaDV       4     1              0
## 176 Network           0 self$bipartite_rsienaDV       6    10              0
## 177 Network           0 self$bipartite_rsienaDV       8     6              0
## 178 Network           0 self$bipartite_rsienaDV       4     9              0
## 179 Network           0 self$bipartite_rsienaDV       9    10              0
## 180 Network           0 self$bipartite_rsienaDV       4     7              0
## 181 Network           0 self$bipartite_rsienaDV       8    10              0
## 182 Network           0 self$bipartite_rsienaDV       2    10              0
## 183 Network           0 self$bipartite_rsienaDV       9    10              0
## 184 Network           0 self$bipartite_rsienaDV       6     9              0
## 185 Network           0 self$bipartite_rsienaDV       8     6              0
## 186 Network           0 self$bipartite_rsienaDV       1     1              0
## 187 Network           0 self$bipartite_rsienaDV       4     7              0
## 188 Network           0 self$bipartite_rsienaDV      12     2              0
## 189 Network           0 self$bipartite_rsienaDV      11     9              0
## 190 Network           0 self$bipartite_rsienaDV       9     9              0
## 191 Network           0 self$bipartite_rsienaDV      11     2              0
## 192 Network           0 self$bipartite_rsienaDV       1     8              0
## 193 Network           0 self$bipartite_rsienaDV       6     7              0
## 194 Network           0 self$bipartite_rsienaDV       6     3              0
## 195 Network           0 self$bipartite_rsienaDV       9     2              0
## 196 Network           0 self$bipartite_rsienaDV      11     4              0
## 197 Network           0 self$bipartite_rsienaDV      12     7              0
## 198 Network           0 self$bipartite_rsienaDV       7     5              0
## 199 Network           0 self$bipartite_rsienaDV      11     2              0
## 200 Network           0 self$bipartite_rsienaDV       5     1              0
## 201 Network           0 self$bipartite_rsienaDV       2     7              0
## 202 Network           0 self$bipartite_rsienaDV       6     1              0
## 203 Network           0 self$bipartite_rsienaDV       7     8              0
## 204 Network           0 self$bipartite_rsienaDV       8     9              0
## 205 Network           0 self$bipartite_rsienaDV       2     4              0
## 206 Network           0 self$bipartite_rsienaDV      12    10              0
## 207 Network           0 self$bipartite_rsienaDV       1     8              0
## 208 Network           0 self$bipartite_rsienaDV       9    10              0
## 209 Network           0 self$bipartite_rsienaDV       6     1              0
## 210 Network           0 self$bipartite_rsienaDV      10     8              0
## 211 Network           0 self$bipartite_rsienaDV       6     6              0
## 212 Network           0 self$bipartite_rsienaDV      12     3              0
## 213 Network           0 self$bipartite_rsienaDV       9     2              0
## 214 Network           0 self$bipartite_rsienaDV       4    10              0
## 215 Network           0 self$bipartite_rsienaDV       2     1              0
## 216 Network           0 self$bipartite_rsienaDV      10     8              0
## 217 Network           0 self$bipartite_rsienaDV       9     7              0
## 218 Network           0 self$bipartite_rsienaDV      11     4              0
## 219 Network           0 self$bipartite_rsienaDV       8     4              0
## 220 Network           0 self$bipartite_rsienaDV       3     8              0
## 221 Network           0 self$bipartite_rsienaDV       6     5              0
## 222 Network           0 self$bipartite_rsienaDV       5     8              0
## 223 Network           0 self$bipartite_rsienaDV       8     2              0
## 224 Network           0 self$bipartite_rsienaDV       2     3              0
## 225 Network           0 self$bipartite_rsienaDV      10     5              0
## 226 Network           0 self$bipartite_rsienaDV      10     2              0
## 227 Network           0 self$bipartite_rsienaDV       2     7              0
## 228 Network           0 self$bipartite_rsienaDV       2     6              0
## 229 Network           0 self$bipartite_rsienaDV       3     1              0
## 230 Network           0 self$bipartite_rsienaDV       3     5              0
## 231 Network           0 self$bipartite_rsienaDV       9     9              0
## 232 Network           0 self$bipartite_rsienaDV       9     3              0
## 233 Network           0 self$bipartite_rsienaDV       7     3              0
## 234 Network           0 self$bipartite_rsienaDV       7     2              0
## 235 Network           0 self$bipartite_rsienaDV      12    10              0
## 236 Network           0 self$bipartite_rsienaDV       3     4              0
## 237 Network           0 self$bipartite_rsienaDV       8     3              0
## 238 Network           0 self$bipartite_rsienaDV       6     9              0
## 239 Network           0 self$bipartite_rsienaDV       8     2              0
## 240 Network           0 self$bipartite_rsienaDV       8    10              0
## 241 Network           0 self$bipartite_rsienaDV       3    10              0
## 242 Network           0 self$bipartite_rsienaDV      10     5              0
## 243 Network           0 self$bipartite_rsienaDV       1    10              0
## 244 Network           0 self$bipartite_rsienaDV       8     4              0
## 245 Network           0 self$bipartite_rsienaDV       5     6              0
## 246 Network           0 self$bipartite_rsienaDV      11     4              0
## 247 Network           0 self$bipartite_rsienaDV       2     2              0
## 248 Network           0 self$bipartite_rsienaDV       1     2              0
## 249 Network           0 self$bipartite_rsienaDV       4     2              0
## 250 Network           0 self$bipartite_rsienaDV      10     2              0
## 251 Network           0 self$bipartite_rsienaDV       1     4              0
## 252 Network           0 self$bipartite_rsienaDV      11     2              0
## 253 Network           0 self$bipartite_rsienaDV       9     5              0
## 254 Network           0 self$bipartite_rsienaDV       3     4              0
## 255 Network           0 self$bipartite_rsienaDV       5     1              0
## 256 Network           0 self$bipartite_rsienaDV       5     6              0
## 257 Network           0 self$bipartite_rsienaDV       4     2              0
## 258 Network           0 self$bipartite_rsienaDV       6     9              0
## 259 Network           0 self$bipartite_rsienaDV       8     2              0
## 260 Network           0 self$bipartite_rsienaDV       1     4              0
## 261 Network           0 self$bipartite_rsienaDV       8     5              0
## 262 Network           0 self$bipartite_rsienaDV       1    10              0
## 263 Network           0 self$bipartite_rsienaDV       7     8              0
## 264 Network           0 self$bipartite_rsienaDV       4     4              0
## 265 Network           0 self$bipartite_rsienaDV       3     4              0
## 266 Network           0 self$bipartite_rsienaDV       5     5              0
## 267 Network           0 self$bipartite_rsienaDV       6     7              0
## 268 Network           0 self$bipartite_rsienaDV       5     1              0
## 269 Network           0 self$bipartite_rsienaDV       8    10              0
## 270 Network           0 self$bipartite_rsienaDV      12     6              0
## 271 Network           0 self$bipartite_rsienaDV       7     5              0
## 272 Network           0 self$bipartite_rsienaDV      11     2              0
## 273 Network           0 self$bipartite_rsienaDV       5     4              0
## 274 Network           0 self$bipartite_rsienaDV       9     5              0
## 275 Network           0 self$bipartite_rsienaDV       8     3              0
## 276 Network           0 self$bipartite_rsienaDV      11     5              0
## 277 Network           0 self$bipartite_rsienaDV       1     9              0
## 278 Network           0 self$bipartite_rsienaDV       4     2              0
## 279 Network           0 self$bipartite_rsienaDV      12    10              0
## 280 Network           0 self$bipartite_rsienaDV       5     9              0
## 281 Network           0 self$bipartite_rsienaDV       1     8              0
## 282 Network           0 self$bipartite_rsienaDV      10     1              0
## 283 Network           0 self$bipartite_rsienaDV       2     3              0
## 284 Network           0 self$bipartite_rsienaDV      11     5              0
## 285 Network           0 self$bipartite_rsienaDV       8     6              0
## 286 Network           0 self$bipartite_rsienaDV       9     9              0
## 287 Network           0 self$bipartite_rsienaDV       6     1              0
## 288 Network           0 self$bipartite_rsienaDV       9     7              0
## 289 Network           0 self$bipartite_rsienaDV      10     8              0
## 290 Network           0 self$bipartite_rsienaDV       4     6              0
## 291 Network           0 self$bipartite_rsienaDV       8    10              0
## 292 Network           0 self$bipartite_rsienaDV       8     4              0
## 293 Network           0 self$bipartite_rsienaDV       5     6              0
## 294 Network           0 self$bipartite_rsienaDV       6     5              0
## 295 Network           0 self$bipartite_rsienaDV       1     4              0
## 296 Network           0 self$bipartite_rsienaDV      12    10              0
## 297 Network           0 self$bipartite_rsienaDV       1     4              0
## 298 Network           0 self$bipartite_rsienaDV       9     5              0
## 299 Network           0 self$bipartite_rsienaDV      10     5              0
## 300 Network           0 self$bipartite_rsienaDV       7     2              0
##     reciprocal_rate LogOptionSetProb LogChoiceProb diagonal stability
## 1        0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 2        0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 3        0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 4        0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 5        0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 6        0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 7        0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 8        0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 9        0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 10       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 11       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 12       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 13       0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 14       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 15       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 16       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 17       0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 18       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 19       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 20       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 21       0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 22       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 23       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 24       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 25       0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 26       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 27       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 28       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 29       0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 30       0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 31       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 32       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 33       0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 34       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 35       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 36       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 37       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 38       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 39       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 40       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 41       0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 42       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 43       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 44       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 45       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 46       0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 47       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 48       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 49       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 50       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 51       0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 52       0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 53       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 54       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 55       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 56       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 57       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 58       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 59       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 60       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 61       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 62       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 63       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 64       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 65       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 66       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 67       0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 68       0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 69       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 70       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 71       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 72       0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 73       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 74       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 75       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 76       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 77       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 78       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 79       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 80       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 81       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 82       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 83       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 84       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 85       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 86       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 87       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 88       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 89       0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 90       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 91       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 92       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 93       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 94       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 95       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 96       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 97       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 98       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 99       0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 100      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 101      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 102      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 103      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 104      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 105      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 106      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 107      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 108      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 109      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 110      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 111      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 112      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 113      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 114      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 115      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 116      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 117      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 118      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 119      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 120      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 121      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 122      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 123      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 124      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 125      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 126      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 127      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 128      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 129      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 130      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 131      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 132      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 133      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 134      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 135      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 136      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 137      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 138      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 139      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 140      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 141      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 142      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 143      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 144      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 145      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 146      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 147      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 148      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 149      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 150      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 151      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 152      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 153      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 154      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 155      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 156      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 157      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 158      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 159      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 160      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 161      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 162      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 163      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 164      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 165      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 166      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 167      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 168      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 169      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 170      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 171      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 172      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 173      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 174      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 175      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 176      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 177      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 178      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 179      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 180      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 181      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 182      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 183      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 184      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 185      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 186      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 187      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 188      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 189      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 190      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 191      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 192      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 193      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 194      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 195      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 196      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 197      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 198      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 199      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 200      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 201      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 202      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 203      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 204      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 205      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 206      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 207      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 208      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 209      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 210      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 211      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 212      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 213      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 214      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 215      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 216      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 217      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 218      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 219      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 220      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 221      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 222      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 223      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 224      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 225      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 226      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 227      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 228      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 229      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 230      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 231      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 232      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 233      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 234      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 235      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 236      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 237      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 238      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 239      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 240      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 241      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 242      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 243      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 244      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 245      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 246      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 247      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 248      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 249      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 250      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 251      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 252      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 253      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 254      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 255      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 256      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 257      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 258      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 259      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 260      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 261      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 262      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 263      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 264      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 265      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 266      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 267      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 268      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 269      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 270      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 271      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 272      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 273      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 274      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 275      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 276      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 277      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 278      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 279      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 280      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 281      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 282      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 283      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 284      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 285      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 286      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 287      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 288      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 289      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 290      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 291      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 292      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 293      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 294      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 295      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 296      0.08333333        -2.484907     -2.302585    FALSE      TRUE
## 297      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 298      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 299      0.08333333        -2.484907     -2.302585    FALSE     FALSE
## 300      0.08333333        -2.484907     -2.302585    FALSE     FALSE
##     tie_change chain_step_id
## 1         TRUE             1
## 2         TRUE             2
## 3         TRUE             3
## 4         TRUE             4
## 5         TRUE             5
## 6        FALSE             5
## 7         TRUE             7
## 8         TRUE             8
## 9         TRUE             9
## 10        TRUE            10
## 11        TRUE            11
## 12        TRUE            12
## 13       FALSE            12
## 14        TRUE            14
## 15        TRUE            15
## 16        TRUE            16
## 17       FALSE            16
## 18        TRUE            18
## 19        TRUE            19
## 20        TRUE            20
## 21       FALSE            20
## 22        TRUE            22
## 23        TRUE            23
## 24        TRUE            24
## 25       FALSE            24
## 26        TRUE            26
## 27        TRUE            27
## 28        TRUE            28
## 29       FALSE            28
## 30       FALSE            28
## 31        TRUE            31
## 32        TRUE            32
## 33       FALSE            32
## 34        TRUE            34
## 35        TRUE            35
## 36        TRUE            36
## 37        TRUE            37
## 38        TRUE            38
## 39        TRUE            39
## 40        TRUE            40
## 41       FALSE            40
## 42        TRUE            42
## 43        TRUE            43
## 44        TRUE            44
## 45        TRUE            45
## 46       FALSE            45
## 47        TRUE            47
## 48        TRUE            48
## 49        TRUE            49
## 50        TRUE            50
## 51       FALSE            50
## 52       FALSE            50
## 53        TRUE            53
## 54        TRUE            54
## 55        TRUE            55
## 56        TRUE            56
## 57        TRUE            57
## 58        TRUE            58
## 59        TRUE            59
## 60        TRUE            60
## 61        TRUE            61
## 62        TRUE            62
## 63        TRUE            63
## 64        TRUE            64
## 65        TRUE            65
## 66        TRUE            66
## 67       FALSE            66
## 68       FALSE            66
## 69        TRUE            69
## 70        TRUE            70
## 71        TRUE            71
## 72       FALSE            71
## 73        TRUE            73
## 74        TRUE            74
## 75        TRUE            75
## 76        TRUE            76
## 77        TRUE            77
## 78        TRUE            78
## 79        TRUE            79
## 80        TRUE            80
## 81        TRUE            81
## 82        TRUE            82
## 83        TRUE            83
## 84        TRUE            84
## 85        TRUE            85
## 86        TRUE            86
## 87        TRUE            87
## 88        TRUE            88
## 89       FALSE            88
## 90        TRUE            90
## 91        TRUE            91
## 92        TRUE            92
## 93        TRUE            93
## 94        TRUE            94
## 95        TRUE            95
## 96        TRUE            96
## 97        TRUE            97
## 98        TRUE            98
## 99        TRUE            99
## 100       TRUE           100
## 101      FALSE           100
## 102       TRUE           102
## 103       TRUE           103
## 104       TRUE           104
## 105       TRUE           105
## 106       TRUE           106
## 107       TRUE           107
## 108       TRUE           108
## 109       TRUE           109
## 110       TRUE           110
## 111       TRUE           111
## 112       TRUE           112
## 113       TRUE           113
## 114       TRUE           114
## 115       TRUE           115
## 116       TRUE           116
## 117       TRUE           117
## 118       TRUE           118
## 119       TRUE           119
## 120       TRUE           120
## 121       TRUE           121
## 122       TRUE           122
## 123       TRUE           123
## 124      FALSE           123
## 125       TRUE           125
## 126       TRUE           126
## 127       TRUE           127
## 128       TRUE           128
## 129       TRUE           129
## 130       TRUE           130
## 131       TRUE           131
## 132       TRUE           132
## 133       TRUE           133
## 134       TRUE           134
## 135       TRUE           135
## 136       TRUE           136
## 137       TRUE           137
## 138      FALSE           137
## 139       TRUE           139
## 140       TRUE           140
## 141       TRUE           141
## 142       TRUE           142
## 143       TRUE           143
## 144       TRUE           144
## 145      FALSE           144
## 146       TRUE           146
## 147       TRUE           147
## 148      FALSE           147
## 149       TRUE           149
## 150       TRUE           150
## 151       TRUE           151
## 152       TRUE           152
## 153       TRUE           153
## 154       TRUE           154
## 155       TRUE           155
## 156       TRUE           156
## 157      FALSE           156
## 158       TRUE           158
## 159       TRUE           159
## 160       TRUE           160
## 161       TRUE           161
## 162       TRUE           162
## 163       TRUE           163
## 164       TRUE           164
## 165       TRUE           165
## 166      FALSE           165
## 167       TRUE           167
## 168       TRUE           168
## 169       TRUE           169
## 170       TRUE           170
## 171       TRUE           171
## 172       TRUE           172
## 173       TRUE           173
## 174       TRUE           174
## 175       TRUE           175
## 176      FALSE           175
## 177       TRUE           177
## 178       TRUE           178
## 179      FALSE           178
## 180       TRUE           180
## 181      FALSE           180
## 182      FALSE           180
## 183      FALSE           180
## 184       TRUE           184
## 185       TRUE           185
## 186       TRUE           186
## 187       TRUE           187
## 188       TRUE           188
## 189       TRUE           189
## 190       TRUE           190
## 191       TRUE           191
## 192       TRUE           192
## 193       TRUE           193
## 194       TRUE           194
## 195       TRUE           195
## 196       TRUE           196
## 197       TRUE           197
## 198       TRUE           198
## 199       TRUE           199
## 200       TRUE           200
## 201       TRUE           201
## 202       TRUE           202
## 203       TRUE           203
## 204       TRUE           204
## 205       TRUE           205
## 206      FALSE           205
## 207       TRUE           207
## 208      FALSE           207
## 209       TRUE           209
## 210       TRUE           210
## 211       TRUE           211
## 212       TRUE           212
## 213       TRUE           213
## 214      FALSE           213
## 215       TRUE           215
## 216       TRUE           216
## 217       TRUE           217
## 218       TRUE           218
## 219       TRUE           219
## 220       TRUE           220
## 221       TRUE           221
## 222       TRUE           222
## 223       TRUE           223
## 224       TRUE           224
## 225       TRUE           225
## 226       TRUE           226
## 227       TRUE           227
## 228       TRUE           228
## 229       TRUE           229
## 230       TRUE           230
## 231       TRUE           231
## 232       TRUE           232
## 233       TRUE           233
## 234       TRUE           234
## 235      FALSE           234
## 236       TRUE           236
## 237       TRUE           237
## 238       TRUE           238
## 239       TRUE           239
## 240      FALSE           239
## 241      FALSE           239
## 242       TRUE           242
## 243      FALSE           242
## 244       TRUE           244
## 245       TRUE           245
## 246       TRUE           246
## 247       TRUE           247
## 248       TRUE           248
## 249       TRUE           249
## 250       TRUE           250
## 251       TRUE           251
## 252       TRUE           252
## 253       TRUE           253
## 254       TRUE           254
## 255       TRUE           255
## 256       TRUE           256
## 257       TRUE           257
## 258       TRUE           258
## 259       TRUE           259
## 260       TRUE           260
## 261       TRUE           261
## 262      FALSE           261
## 263       TRUE           263
## 264       TRUE           264
## 265       TRUE           265
## 266       TRUE           266
## 267       TRUE           267
## 268       TRUE           268
## 269      FALSE           268
## 270       TRUE           270
## 271       TRUE           271
## 272       TRUE           272
## 273       TRUE           273
## 274       TRUE           274
## 275       TRUE           275
## 276       TRUE           276
## 277       TRUE           277
## 278       TRUE           278
## 279      FALSE           278
## 280       TRUE           280
## 281       TRUE           281
## 282       TRUE           282
## 283       TRUE           283
## 284       TRUE           284
## 285       TRUE           285
## 286       TRUE           286
## 287       TRUE           287
## 288       TRUE           288
## 289       TRUE           289
## 290       TRUE           290
## 291      FALSE           290
## 292       TRUE           292
## 293       TRUE           293
## 294       TRUE           294
## 295       TRUE           295
## 296      FALSE           295
## 297       TRUE           297
## 298       TRUE           298
## 299       TRUE           299
## 300       TRUE           300
## 
##  33.33%
##  66.67%
##  100.00%
## ===================================================================================================
##                                                                               Model 1              
## ---------------------------------------------------------------------------------------------------
## Rate parameter period 1                                                         0.0792 (0.0787)    
## outdegree (density)                                                             0.0000 (0.0000)    
## indegree - popularity                                                           0.0000 (0.0000)    
## outdegree - activity                                                            0.0000 (0.0000)    
## XW=>X closure of self$component_1_coDyadCovar                                   1.0000 (0.0000) ***
## self$component_2_coDyadCovar                                                    0.0000 (0.0000)    
## self$strat_1_coCovar ego                                                        0.0000 (0.0000)    
## ind. pop.^(1/0) weighted self$strat_2_coCovar                                   0.0000 (0.0000)    
## self$strat_1_coCovar ego x XW=>X closure of self$component_1_coDyadCovar        0.0000 (0.0000)    
## ind. pop.^(1/0) weighted self$strat_2_coCovar x self$component_2_coDyadCovar    0.0000 (0.0000)    
## ---------------------------------------------------------------------------------------------------
## Iterations                                                                    300                  
## ===================================================================================================
## *** p < 0.001; ** p < 0.01; * p < 0.05
## 1st and last state of the bipartite matrix system
print(env1$bipartite_matrix_init )
##       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
##  [1,]    0    0    0    0    0    0    0    0    0
##  [2,]    0    0    0    0    0    0    0    0    0
##  [3,]    0    0    0    0    0    0    0    0    0
##  [4,]    0    0    0    0    0    0    0    0    0
##  [5,]    0    0    0    0    0    0    0    0    0
##  [6,]    0    0    0    0    0    0    0    0    0
##  [7,]    0    0    0    0    0    0    0    0    0
##  [8,]    0    0    0    0    0    0    0    0    0
##  [9,]    0    0    0    0    0    0    0    0    0
## [10,]    0    0    0    0    0    0    0    0    0
## [11,]    0    0    0    0    0    0    0    0    0
## [12,]    0    0    0    0    0    0    0    0    0
print(env1$bi_env_arr[,, dim(env1$bi_env_arr)[3] ] )
##       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
##  [1,]    1    1    0    0    1    1    0    1    0
##  [2,]    1    0    1    0    0    1    0    0    1
##  [3,]    1    1    0    0    0    0    0    0    0
##  [4,]    0    0    1    0    0    1    0    0    0
##  [5,]    0    0    1    0    0    0    0    0    0
##  [6,]    1    1    1    0    0    1    0    0    0
##  [7,]    0    1    1    0    1    0    0    1    1
##  [8,]    1    0    1    1    0    1    1    0    1
##  [9,]    1    1    1    1    0    1    1    1    0
## [10,]    0    1    1    1    1    1    0    1    0
## [11,]    0    0    1    1    0    0    1    1    0
## [12,]    0    1    0    0    1    0    1    1    0

1.5 Plot Actor Degrees (Component Scope and Common Affiliation Social Ties)

Time series is simulated decision steps.

##
env1$plot_actor_degrees(loess_span = 0.35)
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'

1.6 Plot Component Degrees (Membership/Popularity and Common Actor Epistasis Ties)

##
env1$plot_component_degrees(loess_span = 0.35)
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'

1.7 Plot Utility by Strategy over Time (Simulated Decision Steps)

## [1] 3600    5
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'

1.8 Plot Utility by Actor over Time (Simulated Decision Steps)

## [1] 3600    5
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'

1.9 Plot Contributions to Actor Utility colored by Strategy

Time series is simulated decision steps.

##
env1$plot_utility_components(loess_span=0.25)
## `geom_smooth()` using formula = 'y ~ x'

1.10 Plot Actor Utility Timeseries and Distribution by Strategy

env1$plot_actor_utility_strategy_summary(loess_span=0.5)

1.11 Fitness Landscape Peaks Distributions

Number of changes to component ties as distance from counterfactual affiliation configurations

## Use random uniform values for all combinations like traditional NK model
env1$compute_fitness_landscape(component_coCovar=NA)
## 
## The mean number of peaks per landscape is: 80.73333 
## 
## The std. deviation of the number of peaks per landscape is: 18.62874 
## 
## The skewness of the number of peaks per landscape is: -0.03144415 
## 
## The kurtosis of the number of peaks per landscape is: -1.06321 
## 
## Elapsed time: 2.29 sec
## Use the component values as the means of random noise for different payoff combinations 
# env1$compute_fitness_landscape(component_coCovar=1)
## LOWER SD of component values noise for different payoff combinations 
# env1$compute_fitness_landscape(component_coCovar=1, component_value_sd=0.01)
## HIGHER SD of component values noise for different payoff combinations 
# env1$compute_fitness_landscape(component_coCovar=1, component_value_sd=0.5)

2. Environmental WITH Endogenous Noise

Structural Effects in range [-1, 0.4]

2.1 Environmental Configuration

Reuse existing environ_config

2.2 Structrual Model

SAOM Objective Function serves as the stochastic actor’s utility function for strategic search.

strategies <- list(
  egoX   =   c(-1, 0, 1),
  inPopX =   c( 1, 0, -1)
)

## 2.b. Component Payoffs vector
set.seed(12345)
component_payoffs <-  runif(environ_params$N, min = 0, max = 1)
## 2. Strategies sets the objective function as a linear combination of network stats across DVs
#
actor_strats_list <- lapply(strategies, function(strat) rep(strat,  environ_params$M/length(strat)) )

component_int_mat <- create_block_diag(environ_params$N, round(environ_params$N/3))

# dyad_cov_XWX <- ( outer(component_payoffs, component_payoffs, '*') * 
#     create_block_diag(environ_params$N, round(environ_params$N/3))
# )
dyad_cov_X <- matrix(runif(n = environ_params$N*environ_params$M, min = -.5, max= 1), nrow=environ_params$M) 
# dyad_cov_XWX_X <- t( dyad_cov_XWX %*% t(dyad_cov_X) )

#
structure_model <- list(
  dv_bipartite = list(
    name = 'self$bipartite_rsienaDV',
    effects = list( ##**STRUCTURAL EFFECTS -- dyadic/network endogeneity sources**
      list(effect='density', parameter= -.5, dv_name=DV_NAME, fix=T ), ##interaction1 = NULL
      list(effect='inPop',   parameter= .1, dv_name=DV_NAME, fix=T ), #interaction1 = NUL
      list(effect='outAct',  parameter= .1, dv_name=DV_NAME, fix=T )
    ),
    ## COVARIATE EFFECTS
    coCovars = list( 
      ##** COMPONENTS : MONADIC CONSTANT COVARIATE EFFECTS **##
      # list(effect='altX',   parameter= 0, dv_name=DV_NAME, fix=T,
      #      interaction1='self$component_1_coCovar', x = component_payoffs 
      # ),
      # list(effect='outActX',   parameter= 0, dv_name=DV_NAME, fix=T,
      #      interaction1='self$component_1_coCovar', x = component_payoffs 
      # ),
      ##** STRATEGIES : MONADIC CONSTANT COVARIATE EFFECTS **##
      list(effect='egoX',   parameter= .1,  dv_name=DV_NAME, fix=T,
           interaction1='self$strat_1_coCovar',   x = actor_strats_list[[1]] 
      ), #interaction1 = NULL
      list(effect='inPopX', parameter= .1,  dv_name=DV_NAME, fix=T,
           interaction1='self$strat_2_coCovar',  x = actor_strats_list[[2]] 
      ) #,
      # list(effect='totInDist2', parameter= 0,  dv_name=DV_NAME, fix=T,
      #      interaction1='self$strat_3_coCovar',  x = (actor_strats_list[[1]] - actor_strats_list[[2]] )
      # )
    ),
    ##**MONADIC TIME-VARYING COVARIATE EFFECTS -- DYNAMIC STRATEGY PROGRAMS**
    varCovars = list(),
    ##**DYADIC CONSTANT COVARIATE EFFECTS -- EXOGENOUS INTERACTION MATRIX**
    coDyadCovars = list(
      list(effect='XWX',   parameter= 1, dv_name=DV_NAME, fix=T,
           interaction1='self$component_1_coDyadCovar',
           x = component_int_mat ## component-[actor]-component dyads
      ) ,
      list(effect='X',   parameter= 0, dv_name=DV_NAME, fix=T,
           interaction1='self$component_2_coDyadCovar',
           x = dyad_cov_X ## deltas = changes of payoff contributions from each actor-component
      )
    ),
     ##**DYADIC TIME-VARYING COVARIATE EFFECTS -- DYNAMIC INTERACTION MATRIX**
    varDyadCovars = list(),
    interactions = list(
      list(effect='egoX|XWX',   parameter= .5, dv_name=DV_NAME, fix=T,
           interaction1='self$strat_1_coCovar',
           interaction2='self$component_1_coDyadCovar'
      ),
      list(effect='inPopX|X',   parameter= .5, dv_name=DV_NAME, fix=T,
           interaction1='self$strat_2_coCovar',
           interaction2='self$component_2_coDyadCovar'
      )
    )
  )
)

2.3 Run RSiena Search Process

env2 <- SaomNkRSienaBiEnv$new(environ_params)
## 
## TEST FROM CALLED CLASS INIT *BEFORE* BASE INIT
## 
## CALLED _BASE_ INIT
## 
## TEST FROM CALLED CLASS INIT *AFTER* BASE INIT
## Run Rsiena search using variable parameters in theta_matrix
env2$search_rsiena(
  structure_model,
  iterations = env1$M * steps_per_actor,
  digits = 4,
  run_seed = 12345
)
## $effect
## [1] "XWX"
## 
## $parameter
## [1] 1
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$component_1_coDyadCovar"
## 
## $x
##       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
##  [1,]    1    1    1    0    0    0    0    0    0
##  [2,]    1    1    1    0    0    0    0    0    0
##  [3,]    1    1    1    0    0    0    0    0    0
##  [4,]    0    0    0    1    1    1    0    0    0
##  [5,]    0    0    0    1    1    1    0    0    0
##  [6,]    0    0    0    1    1    1    0    0    0
##  [7,]    0    0    0    0    0    0    1    1    1
##  [8,]    0    0    0    0    0    0    1    1    1
##  [9,]    0    0    0    0    0    0    1    1    1
## 
## $effect
## [1] "X"
## 
## $parameter
## [1] 0
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$component_2_coDyadCovar"
## 
## $x
##              [,1]         [,2]        [,3]        [,4]       [,5]         [,6]
##  [1,]  0.98460541 -0.009871387  0.52275043 -0.01816299 -0.3794959  0.919646128
##  [2,] -0.44819685  0.948122985  0.05515619 -0.40970726  0.1532957  0.532530035
##  [3,] -0.27143976  0.561222816  0.04243836 -0.43481532 -0.1451293  0.258300585
##  [4,]  0.60352743  0.466813955  0.80319235 -0.41741927  0.6873517  0.059404367
##  [5,] -0.49829512  0.084742727  0.85623200  0.43831420 -0.1119735  0.003707558
##  [6,]  0.08680500  0.547815459  0.42613685  0.94670543  0.9789757 -0.427622971
##  [7,]  0.19374198  0.316086797 -0.29895255  0.74095430  0.6353106  0.428421309
##  [8,]  0.08221597 -0.160299232  0.67328992 -0.02745765  0.9696674  0.942170938
##  [9,]  0.10372771  0.226836633  0.14379823 -0.18046182 -0.1715782  0.482440764
## [10,] -0.23155462  0.689510755  0.89091096  0.59874418  0.9230608  0.265437987
## [11,]  0.92748813 -0.491018556  0.65986484  0.24886153 -0.2758131 -0.274852684
## [12,]  0.18059211 -0.218431331 -0.11047813  0.59465796  0.4005355  0.805671821
##              [,7]       [,8]        [,9]
##  [1,]  0.27166252  0.4013924  0.85375569
##  [2,] -0.48702813  0.5721698  0.45618165
##  [3,] -0.47120785  0.2707685  0.79645170
##  [4,] -0.28323215  0.5801748 -0.12332339
##  [5,] -0.04245237  0.6249194 -0.17739638
##  [6,]  0.73848529 -0.3565392  0.41421407
##  [7,]  0.25351696  0.0967388  0.07516695
##  [8,]  0.70535894 -0.0583019  0.63290657
##  [9,] -0.40904003  0.4258805  0.06960436
## [10,]  0.89193270  0.9614112  0.69245810
## [11,]  0.71226783  0.4273181  0.85853670
## [12,] -0.38177999  0.2820538  0.97603926
## 
## 
## 
## self$rsiena_data : 
## 
## Dependent variables:  self$bipartite_rsienaDV 
## Number of observations: 2 
## 
## Nodesets                 ACTORS      COMPONENTS 
## Number of nodes              12               9 
## 
## Dependent variable self$bipartite_rsienaDV
## Type               bipartite              
## Observations       2                      
## First nodeset      ACTORS                 
## Second nodeset     COMPONENTS             
## Densities          NA NA                  
## 
## Constant covariates:  self$strat_1_coCovar, self$strat_2_coCovar 
## Constant dyadic covariates:  self$component_1_coDyadCovar, self$component_2_coDyadCovar 
## 
##  structural effects i=1, j=1
## $effect
## [1] "density"
## 
## $parameter
## [1] -0.5
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
##   effectName          include fix  test  initialValue parm
## 1 outdegree (density) TRUE    TRUE FALSE   -1.60944   0   
##   effectName          include fix  test  initialValue parm
## 1 outdegree (density) TRUE    TRUE FALSE          0   -0.5
## 
##  structural effects i=1, j=2
## $effect
## [1] "inPop"
## 
## $parameter
## [1] 0.1
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
##   effectName            include fix  test  initialValue parm
## 1 indegree - popularity TRUE    TRUE FALSE          0   0   
##   effectName            include fix  test  initialValue parm
## 1 indegree - popularity TRUE    TRUE FALSE          0   0.1 
## 
##  structural effects i=1, j=3
## $effect
## [1] "outAct"
## 
## $parameter
## [1] 0.1
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
##   effectName           include fix  test  initialValue parm
## 1 outdegree - activity TRUE    TRUE FALSE          0   0   
##   effectName           include fix  test  initialValue parm
## 1 outdegree - activity TRUE    TRUE FALSE          0   0.1 
## 
##  coCovars i=1, j=1
## $effect
## [1] "egoX"
## 
## $parameter
## [1] 0.1
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$strat_1_coCovar"
## 
## $x
##  [1] -1  0  1 -1  0  1 -1  0  1 -1  0  1
## 
##   effectName               include fix  test  initialValue parm
## 1 self$strat_1_coCovar ego TRUE    TRUE FALSE          0   0   
##   effectName               include fix  test  initialValue parm
## 1 self$strat_1_coCovar ego TRUE    TRUE FALSE          0   0.1 
## 
##  coCovars i=1, j=2
## $effect
## [1] "inPopX"
## 
## $parameter
## [1] 0.1
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$strat_2_coCovar"
## 
## $x
##  [1]  1  0 -1  1  0 -1  1  0 -1  1  0 -1
## 
##   effectName                                    include fix  test  initialValue
## 1 ind. pop.^(1/#) weighted self$strat_2_coCovar TRUE    TRUE FALSE          0  
##   parm
## 1 1   
##   effectName                                    include fix  test  initialValue
## 1 ind. pop.^(1/#) weighted self$strat_2_coCovar TRUE    TRUE FALSE          0  
##   parm
## 1 0.1 
## 
##  coDyadCovars i=1, j=1
## $effect
## [1] "XWX"
## 
## $parameter
## [1] 1
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$component_1_coDyadCovar"
## 
## $x
##       [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9]
##  [1,]    1    1    1    0    0    0    0    0    0
##  [2,]    1    1    1    0    0    0    0    0    0
##  [3,]    1    1    1    0    0    0    0    0    0
##  [4,]    0    0    0    1    1    1    0    0    0
##  [5,]    0    0    0    1    1    1    0    0    0
##  [6,]    0    0    0    1    1    1    0    0    0
##  [7,]    0    0    0    0    0    0    1    1    1
##  [8,]    0    0    0    0    0    0    1    1    1
##  [9,]    0    0    0    0    0    0    1    1    1
## 
##   effectName                                    include fix  test  initialValue
## 1 XW=>X closure of self$component_1_coDyadCovar TRUE    TRUE FALSE          0  
##   parm
## 1 0   
##   effectName                                    include fix  test  initialValue
## 1 XW=>X closure of self$component_1_coDyadCovar TRUE    TRUE FALSE          0  
##   parm
## 1 1   
## 
##  coDyadCovars i=1, j=2
## $effect
## [1] "X"
## 
## $parameter
## [1] 0
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$component_2_coDyadCovar"
## 
## $x
##              [,1]         [,2]        [,3]        [,4]       [,5]         [,6]
##  [1,]  0.98460541 -0.009871387  0.52275043 -0.01816299 -0.3794959  0.919646128
##  [2,] -0.44819685  0.948122985  0.05515619 -0.40970726  0.1532957  0.532530035
##  [3,] -0.27143976  0.561222816  0.04243836 -0.43481532 -0.1451293  0.258300585
##  [4,]  0.60352743  0.466813955  0.80319235 -0.41741927  0.6873517  0.059404367
##  [5,] -0.49829512  0.084742727  0.85623200  0.43831420 -0.1119735  0.003707558
##  [6,]  0.08680500  0.547815459  0.42613685  0.94670543  0.9789757 -0.427622971
##  [7,]  0.19374198  0.316086797 -0.29895255  0.74095430  0.6353106  0.428421309
##  [8,]  0.08221597 -0.160299232  0.67328992 -0.02745765  0.9696674  0.942170938
##  [9,]  0.10372771  0.226836633  0.14379823 -0.18046182 -0.1715782  0.482440764
## [10,] -0.23155462  0.689510755  0.89091096  0.59874418  0.9230608  0.265437987
## [11,]  0.92748813 -0.491018556  0.65986484  0.24886153 -0.2758131 -0.274852684
## [12,]  0.18059211 -0.218431331 -0.11047813  0.59465796  0.4005355  0.805671821
##              [,7]       [,8]        [,9]
##  [1,]  0.27166252  0.4013924  0.85375569
##  [2,] -0.48702813  0.5721698  0.45618165
##  [3,] -0.47120785  0.2707685  0.79645170
##  [4,] -0.28323215  0.5801748 -0.12332339
##  [5,] -0.04245237  0.6249194 -0.17739638
##  [6,]  0.73848529 -0.3565392  0.41421407
##  [7,]  0.25351696  0.0967388  0.07516695
##  [8,]  0.70535894 -0.0583019  0.63290657
##  [9,] -0.40904003  0.4258805  0.06960436
## [10,]  0.89193270  0.9614112  0.69245810
## [11,]  0.71226783  0.4273181  0.85853670
## [12,] -0.38177999  0.2820538  0.97603926
## 
## There is no effect with short name X, 
## and with interaction1 = <>, interaction2 = <>, and type = <eval>, 
## for dependent variable self$bipartite_rsienaDV .
## See effectsDocumentation() for this effects object.
##   effectName                   include fix  test  initialValue parm
## 1 self$component_2_coDyadCovar TRUE    TRUE FALSE          0   0   
## 
##  interactions i=1, j=1
## $effect
## [1] "egoX|XWX"
## 
## $parameter
## [1] 0.5
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$strat_1_coCovar"
## 
## $interaction2
## [1] "self$component_1_coDyadCovar"
## 
## $effects
## [1] "egoX" "XWX" 
## 
##   effectName                                                              
## 1 self$strat_1_coCovar ego x XW=>X closure of self$component_1_coDyadCovar
##   include fix  test  initialValue parm effect1 effect2
## 1 TRUE    TRUE FALSE          0   0    88      80     
## 
##  interactions i=1, j=2
## $effect
## [1] "inPopX|X"
## 
## $parameter
## [1] 0.5
## 
## $dv_name
## [1] "self$bipartite_rsienaDV"
## 
## $fix
## [1] TRUE
## 
## $interaction1
## [1] "self$strat_2_coCovar"
## 
## $interaction2
## [1] "self$component_2_coDyadCovar"
## 
## $effects
## [1] "inPopX" "X"     
## 
##   effectName                                                                    
## 1 ind. pop.^(1/0.1) weighted self$strat_2_coCovar x self$component_2_coDyadCovar
##   include fix  test  initialValue parm effect1 effect2
## 1 TRUE    TRUE FALSE          0   0    169     85     
## [1] "density"
## [1] "inPop"
## [1] "outAct"
## [1] "XWX"
## [1] "X"
## [1] "egoX"
## [1] "inPopX"
## [1] "egoX|XWX"
## [1] "inPopX|X"
## 
## 
##  theta_matrix : 
## 
##        density inPop outAct XWX X egoX inPopX egoX|XWX inPopX|X
##   [1,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##   [2,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##   [3,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##   [4,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##   [5,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##   [6,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##   [7,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##   [8,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##   [9,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [10,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [11,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [12,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [13,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [14,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [15,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [16,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [17,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [18,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [19,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [20,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [21,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [22,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [23,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [24,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [25,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [26,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [27,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [28,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [29,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [30,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [31,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [32,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [33,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [34,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [35,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [36,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [37,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [38,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [39,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [40,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [41,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [42,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [43,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [44,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [45,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [46,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [47,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [48,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [49,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [50,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [51,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [52,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [53,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [54,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [55,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [56,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [57,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [58,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [59,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [60,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [61,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
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##  [68,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [69,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [70,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
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##  [72,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
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##  [74,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [75,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [76,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [77,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [78,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [79,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [80,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [81,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [82,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [83,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [84,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [85,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [86,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [87,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [88,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [89,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [90,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [91,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [92,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [93,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
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##  [95,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [96,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [97,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [98,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
##  [99,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [100,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [101,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [102,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [103,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [104,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [105,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [106,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [107,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [108,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [109,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [110,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [111,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [112,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [113,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [114,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [115,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [116,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [117,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [118,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [119,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [120,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [121,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [122,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [123,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [124,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [125,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [126,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [127,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [128,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [129,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [130,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [131,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [132,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [133,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [134,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [135,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [136,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [137,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [138,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [139,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [140,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [141,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [142,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [143,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [144,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [145,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [146,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
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## [266,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [267,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [268,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [269,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [270,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [271,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [272,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [273,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [274,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [275,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [276,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [277,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [278,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [279,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [280,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [281,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [282,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [283,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [284,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [285,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [286,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [287,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [288,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [289,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [290,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [291,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [292,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [293,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [294,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [295,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [296,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [297,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [298,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [299,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## [300,]    -0.5   0.1    0.1   1 0  0.1    0.1      0.5      0.5
## If you use this algorithm object, siena07 will create/use an output file C:/Users/sdr8y/OneDrive - University of Missouri/Research/Search_networks/SaoMNK/R/_test_tutorial_nb__173926283510.txt .
## 
## Start phase 0 
## theta: 0 0 0 0 0 0 0 0 0 
## 
## Start phase 3 
## Phase 3 Iteration 100 Progress 33%
## Phase 3 Iteration 200 Progress 67%
## Phase 3 Iteration 300 Progress 100%
## Parameter values used for simulations
## 
##                                                                                          Mean      Standard      
##                                                                                            value   Deviation     
## 
## Rate parameters: 
##   0       Rate parameter                                                                   NA    ( NA        )   
## 
## Other parameters: 
##   1. eval outdegree (density)                                                            -0.5    ( NA        )   
##   2. eval indegree - popularity                                                           0.1    ( NA        )   
##   3. eval outdegree - activity                                                            0.1    ( NA        )   
##   4. eval XW=>X closure of self$component_1_coDyadCovar                                   1.0    ( NA        )   
##   5. eval self$component_2_coDyadCovar                                                    0.0    ( NA        )   
##   6. eval self$strat_1_coCovar ego                                                        0.1    ( NA        )   
##   7. eval ind. pop.^(1/0.1) weighted self$strat_2_coCovar                                 0.1    ( NA        )   
##   8. eval self$strat_1_coCovar ego x XW=>X closure of self$component_1_coDyadCovar        0.5    ( NA        )   
##   9. eval ind. pop.^(1/0.1) weighted self$strat_2_coCovar x self$component_2_coDyadCovar  0.5    ( NA        )   
## 
## Simulated means and standard deviations
##   1. Number of ties                                                                   0.850    0.358 
##   2. Sum of squared indegrees                                                         0.850    0.358 
##   3. Sum of squared outdegrees                                                        0.850    0.358 
##   4. XW=>X closure of self$component_1_coDyadCovar                                    0.000    0.000 
##   5. Sum of ties x self$component_2_coDyadCovar                                      -0.009    0.408 
##   6. Sum of outdegrees x self$strat_1_coCovar                                        -0.053    0.748 
##   7. indegree pop.^(1/0.1) weighted self$strat_2_coCovar                              0.053    0.748 
##   8. self$strat_1_coCovar ego x XW=>X closure of self$component_1_coDyadCovar         0.000    0.000 
##   9. ind. pop.^(1/0.1) weighted self$strat_2_coCovar x self$component_2_coDyadCovar   0.076    0.309 
## 
## 
## Simulated statistics are in x$sf
## and simulated dependent variables in x$sims, where x is the created object.
## 
## Total of 300 iteration steps.
## 
## Covariance matrix of estimates (correlations below diagonal)
## 
##            0            0            0            0            0            0            0            0            0
##          NaN            0            0            0            0            0            0            0            0
##          NaN          NaN            0            0            0            0            0            0            0
##          NaN          NaN          NaN            0            0            0            0            0            0
##          NaN          NaN          NaN          NaN            0            0            0            0            0
##          NaN          NaN          NaN          NaN          NaN            0            0            0            0
##          NaN          NaN          NaN          NaN          NaN          NaN            0            0            0
##          NaN          NaN          NaN          NaN          NaN          NaN          NaN            0            0
##          NaN          NaN          NaN          NaN          NaN          NaN          NaN          NaN            0
## 
## Derivative matrix of expected statistics X by parameters:
## 
##        0.128        0.128        0.128        0.000        0.000       -0.014        0.014        0.000        0.011
##        0.128        0.128        0.128        0.000        0.000       -0.014        0.014        0.000        0.011
##        0.128        0.128        0.128        0.000        0.000       -0.014        0.014        0.000        0.011
##        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000
##       -0.001       -0.001       -0.001        0.000        0.145       -0.024        0.024        0.000       -0.003
##       -0.001       -0.001       -0.001        0.000       -0.010        0.073       -0.073        0.000        0.000
##        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000
##        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000
##        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000        0.000
## 
## Covariance matrix of X (correlations below diagonal):
## 
##        0.128        0.128        0.128        0.000       -0.001       -0.008        0.008        0.000        0.011
##        1.000        0.128        0.128        0.000       -0.001       -0.008        0.008        0.000        0.011
##        1.000        1.000        0.128        0.000       -0.001       -0.008        0.008        0.000        0.011
##          NaN          NaN          NaN        0.000        0.000        0.000        0.000        0.000        0.000
##       -0.009       -0.009       -0.009          NaN        0.166       -0.077        0.077        0.000       -0.005
##       -0.030       -0.030       -0.030          NaN       -0.252        0.559       -0.559        0.000        0.003
##        0.030        0.030        0.030          NaN        0.252       -1.000        0.559        0.000       -0.003
##          NaN          NaN          NaN          NaN          NaN          NaN          NaN        0.000        0.000
##        0.104        0.104        0.104          NaN       -0.040        0.014       -0.014          NaN        0.095
## 
## 
## 
## Simulated Decision Chain Summary:
## 
##    dv_type           dv_type_bin  dv_varname           id_from      
##  Length:300         Min.   :0    Length:300         Min.   : 1.000  
##  Class :character   1st Qu.:0    Class :character   1st Qu.: 4.000  
##  Mode  :character   Median :0    Mode  :character   Median : 7.000  
##                     Mean   :0                       Mean   : 6.757  
##                     3rd Qu.:0                       3rd Qu.:10.000  
##                     Max.   :0                       Max.   :12.000  
##      id_to       beh_difference reciprocal_rate   LogOptionSetProb
##  Min.   : 1.00   Min.   :0      Min.   :0.08333   Min.   :-2.485  
##  1st Qu.: 3.00   1st Qu.:0      1st Qu.:0.08333   1st Qu.:-2.485  
##  Median : 6.00   Median :0      Median :0.08333   Median :-2.485  
##  Mean   : 5.75   Mean   :0      Mean   :0.08333   Mean   :-2.485  
##  3rd Qu.: 9.00   3rd Qu.:0      3rd Qu.:0.08333   3rd Qu.:-2.485  
##  Max.   :10.00   Max.   :0      Max.   :0.08333   Max.   :-2.485  
##  LogChoiceProb      diagonal         stability       tie_change     
##  Min.   :-2.351   Length:300         Mode :logical   Mode :logical  
##  1st Qu.:-2.351   Class :character   FALSE:255       FALSE:45       
##  Median :-2.337   Mode  :character   TRUE :45        TRUE :255      
##  Mean   :-2.293                                                     
##  3rd Qu.:-2.324                                                     
##  Max.   :-1.951                                                     
##  chain_step_id   
##  Min.   :  1.00  
##  1st Qu.: 75.75  
##  Median :150.50  
##  Mean   :150.33  
##  3rd Qu.:225.25  
##  Max.   :300.00  
## [1] 300  13
##     dv_type dv_type_bin              dv_varname id_from id_to beh_difference
## 1   Network           0 self$bipartite_rsienaDV      11     8              0
## 2   Network           0 self$bipartite_rsienaDV       4     6              0
## 3   Network           0 self$bipartite_rsienaDV      12     1              0
## 4   Network           0 self$bipartite_rsienaDV       9     1              0
## 5   Network           0 self$bipartite_rsienaDV       6     4              0
## 6   Network           0 self$bipartite_rsienaDV       3    10              0
## 7   Network           0 self$bipartite_rsienaDV       9     7              0
## 8   Network           0 self$bipartite_rsienaDV       9     6              0
## 9   Network           0 self$bipartite_rsienaDV       1     2              0
## 10  Network           0 self$bipartite_rsienaDV       5     4              0
## 11  Network           0 self$bipartite_rsienaDV       2     9              0
## 12  Network           0 self$bipartite_rsienaDV       4     4              0
## 13  Network           0 self$bipartite_rsienaDV       8    10              0
## 14  Network           0 self$bipartite_rsienaDV       4     3              0
## 15  Network           0 self$bipartite_rsienaDV       6     8              0
## 16  Network           0 self$bipartite_rsienaDV       6     3              0
## 17  Network           0 self$bipartite_rsienaDV       4    10              0
## 18  Network           0 self$bipartite_rsienaDV      12     3              0
## 19  Network           0 self$bipartite_rsienaDV      12     8              0
## 20  Network           0 self$bipartite_rsienaDV       5     4              0
## 21  Network           0 self$bipartite_rsienaDV       8    10              0
## 22  Network           0 self$bipartite_rsienaDV       7     2              0
## 23  Network           0 self$bipartite_rsienaDV       1     2              0
## 24  Network           0 self$bipartite_rsienaDV      10     6              0
## 25  Network           0 self$bipartite_rsienaDV       1    10              0
## 26  Network           0 self$bipartite_rsienaDV       1     7              0
## 27  Network           0 self$bipartite_rsienaDV       7     8              0
## 28  Network           0 self$bipartite_rsienaDV       2     5              0
## 29  Network           0 self$bipartite_rsienaDV       8    10              0
## 30  Network           0 self$bipartite_rsienaDV       7    10              0
## 31  Network           0 self$bipartite_rsienaDV      11     3              0
## 32  Network           0 self$bipartite_rsienaDV      10     4              0
## 33  Network           0 self$bipartite_rsienaDV      11    10              0
## 34  Network           0 self$bipartite_rsienaDV       1     4              0
## 35  Network           0 self$bipartite_rsienaDV       7     1              0
## 36  Network           0 self$bipartite_rsienaDV       9     9              0
## 37  Network           0 self$bipartite_rsienaDV      10     1              0
## 38  Network           0 self$bipartite_rsienaDV      10     7              0
## 39  Network           0 self$bipartite_rsienaDV       3     1              0
## 40  Network           0 self$bipartite_rsienaDV       7     8              0
## 41  Network           0 self$bipartite_rsienaDV      12    10              0
## 42  Network           0 self$bipartite_rsienaDV       7     9              0
## 43  Network           0 self$bipartite_rsienaDV       3     9              0
## 44  Network           0 self$bipartite_rsienaDV       6     9              0
## 45  Network           0 self$bipartite_rsienaDV       9     7              0
## 46  Network           0 self$bipartite_rsienaDV       6    10              0
## 47  Network           0 self$bipartite_rsienaDV      11     5              0
## 48  Network           0 self$bipartite_rsienaDV       5     8              0
## 49  Network           0 self$bipartite_rsienaDV      12     9              0
## 50  Network           0 self$bipartite_rsienaDV       3     5              0
## 51  Network           0 self$bipartite_rsienaDV       4    10              0
## 52  Network           0 self$bipartite_rsienaDV       5    10              0
## 53  Network           0 self$bipartite_rsienaDV       2     8              0
## 54  Network           0 self$bipartite_rsienaDV      12     1              0
## 55  Network           0 self$bipartite_rsienaDV      10     3              0
## 56  Network           0 self$bipartite_rsienaDV       2     6              0
## 57  Network           0 self$bipartite_rsienaDV      10     1              0
## 58  Network           0 self$bipartite_rsienaDV       7     7              0
## 59  Network           0 self$bipartite_rsienaDV       9     4              0
## 60  Network           0 self$bipartite_rsienaDV      12     5              0
## 61  Network           0 self$bipartite_rsienaDV       7     7              0
## 62  Network           0 self$bipartite_rsienaDV       2     2              0
## 63  Network           0 self$bipartite_rsienaDV       7    10              0
## 64  Network           0 self$bipartite_rsienaDV      11     5              0
## 65  Network           0 self$bipartite_rsienaDV       7     6              0
## 66  Network           0 self$bipartite_rsienaDV       9     6              0
## 67  Network           0 self$bipartite_rsienaDV      12    10              0
## 68  Network           0 self$bipartite_rsienaDV       9    10              0
## 69  Network           0 self$bipartite_rsienaDV       5     9              0
## 70  Network           0 self$bipartite_rsienaDV      11     9              0
## 71  Network           0 self$bipartite_rsienaDV       3     2              0
## 72  Network           0 self$bipartite_rsienaDV      10    10              0
## 73  Network           0 self$bipartite_rsienaDV       1     2              0
## 74  Network           0 self$bipartite_rsienaDV      12     8              0
## 75  Network           0 self$bipartite_rsienaDV       4     2              0
## 76  Network           0 self$bipartite_rsienaDV       5     9              0
## 77  Network           0 self$bipartite_rsienaDV      10     2              0
## 78  Network           0 self$bipartite_rsienaDV       4     5              0
## 79  Network           0 self$bipartite_rsienaDV      10     6              0
## 80  Network           0 self$bipartite_rsienaDV       9     9              0
## 81  Network           0 self$bipartite_rsienaDV      10     3              0
## 82  Network           0 self$bipartite_rsienaDV       1     1              0
## 83  Network           0 self$bipartite_rsienaDV       9     7              0
## 84  Network           0 self$bipartite_rsienaDV       9     3              0
## 85  Network           0 self$bipartite_rsienaDV       5     5              0
## 86  Network           0 self$bipartite_rsienaDV      11     6              0
## 87  Network           0 self$bipartite_rsienaDV       4    10              0
## 88  Network           0 self$bipartite_rsienaDV       9     7              0
## 89  Network           0 self$bipartite_rsienaDV       5    10              0
## 90  Network           0 self$bipartite_rsienaDV       1     2              0
## 91  Network           0 self$bipartite_rsienaDV       9     7              0
## 92  Network           0 self$bipartite_rsienaDV       9     6              0
## 93  Network           0 self$bipartite_rsienaDV      11     9              0
## 94  Network           0 self$bipartite_rsienaDV       8     9              0
## 95  Network           0 self$bipartite_rsienaDV       9     7              0
## 96  Network           0 self$bipartite_rsienaDV       8     6              0
## 97  Network           0 self$bipartite_rsienaDV      10     2              0
## 98  Network           0 self$bipartite_rsienaDV       6     3              0
## 99  Network           0 self$bipartite_rsienaDV       9     9              0
## 100 Network           0 self$bipartite_rsienaDV      10     6              0
## 101 Network           0 self$bipartite_rsienaDV      10    10              0
## 102 Network           0 self$bipartite_rsienaDV       8     5              0
## 103 Network           0 self$bipartite_rsienaDV       6     8              0
## 104 Network           0 self$bipartite_rsienaDV       4     8              0
## 105 Network           0 self$bipartite_rsienaDV      11     7              0
## 106 Network           0 self$bipartite_rsienaDV      11     1              0
## 107 Network           0 self$bipartite_rsienaDV      11     9              0
## 108 Network           0 self$bipartite_rsienaDV       4     3              0
## 109 Network           0 self$bipartite_rsienaDV       5     6              0
## 110 Network           0 self$bipartite_rsienaDV       1     5              0
## 111 Network           0 self$bipartite_rsienaDV       3     7              0
## 112 Network           0 self$bipartite_rsienaDV      11     3              0
## 113 Network           0 self$bipartite_rsienaDV       1     6              0
## 114 Network           0 self$bipartite_rsienaDV       1     1              0
## 115 Network           0 self$bipartite_rsienaDV      10     6              0
## 116 Network           0 self$bipartite_rsienaDV       6     2              0
## 117 Network           0 self$bipartite_rsienaDV       4     3              0
## 118 Network           0 self$bipartite_rsienaDV       5     9              0
## 119 Network           0 self$bipartite_rsienaDV       8     1              0
## 120 Network           0 self$bipartite_rsienaDV       4     1              0
## 121 Network           0 self$bipartite_rsienaDV       1    10              0
## 122 Network           0 self$bipartite_rsienaDV       2     9              0
## 123 Network           0 self$bipartite_rsienaDV       1     8              0
## 124 Network           0 self$bipartite_rsienaDV       1    10              0
## 125 Network           0 self$bipartite_rsienaDV      10     6              0
## 126 Network           0 self$bipartite_rsienaDV      12     3              0
## 127 Network           0 self$bipartite_rsienaDV       2     6              0
## 128 Network           0 self$bipartite_rsienaDV       7     5              0
## 129 Network           0 self$bipartite_rsienaDV       5     9              0
## 130 Network           0 self$bipartite_rsienaDV       4     5              0
## 131 Network           0 self$bipartite_rsienaDV       8     3              0
## 132 Network           0 self$bipartite_rsienaDV       9     8              0
## 133 Network           0 self$bipartite_rsienaDV       2     3              0
## 134 Network           0 self$bipartite_rsienaDV       4     6              0
## 135 Network           0 self$bipartite_rsienaDV       8     2              0
## 136 Network           0 self$bipartite_rsienaDV      10     9              0
## 137 Network           0 self$bipartite_rsienaDV      10     9              0
## 138 Network           0 self$bipartite_rsienaDV      11    10              0
## 139 Network           0 self$bipartite_rsienaDV      11     1              0
## 140 Network           0 self$bipartite_rsienaDV       5     8              0
## 141 Network           0 self$bipartite_rsienaDV       5     4              0
## 142 Network           0 self$bipartite_rsienaDV       4     8              0
## 143 Network           0 self$bipartite_rsienaDV      10     8              0
## 144 Network           0 self$bipartite_rsienaDV      11     7              0
## 145 Network           0 self$bipartite_rsienaDV       7    10              0
## 146 Network           0 self$bipartite_rsienaDV       6     4              0
## 147 Network           0 self$bipartite_rsienaDV       8     8              0
## 148 Network           0 self$bipartite_rsienaDV       2    10              0
## 149 Network           0 self$bipartite_rsienaDV       5     3              0
## 150 Network           0 self$bipartite_rsienaDV       3     6              0
## 151 Network           0 self$bipartite_rsienaDV       7     1              0
## 152 Network           0 self$bipartite_rsienaDV       8     8              0
## 153 Network           0 self$bipartite_rsienaDV      11     4              0
## 154 Network           0 self$bipartite_rsienaDV       3     1              0
## 155 Network           0 self$bipartite_rsienaDV       5     1              0
## 156 Network           0 self$bipartite_rsienaDV       7     8              0
## 157 Network           0 self$bipartite_rsienaDV       4    10              0
## 158 Network           0 self$bipartite_rsienaDV       9     3              0
## 159 Network           0 self$bipartite_rsienaDV       8     6              0
## 160 Network           0 self$bipartite_rsienaDV      11     3              0
## 161 Network           0 self$bipartite_rsienaDV       7     4              0
## 162 Network           0 self$bipartite_rsienaDV       3     4              0
## 163 Network           0 self$bipartite_rsienaDV       9     2              0
## 164 Network           0 self$bipartite_rsienaDV       7     2              0
## 165 Network           0 self$bipartite_rsienaDV      10     3              0
## 166 Network           0 self$bipartite_rsienaDV       3    10              0
## 167 Network           0 self$bipartite_rsienaDV      10     8              0
## 168 Network           0 self$bipartite_rsienaDV       7     8              0
## 169 Network           0 self$bipartite_rsienaDV      10    10              0
## 170 Network           0 self$bipartite_rsienaDV       7     2              0
## 171 Network           0 self$bipartite_rsienaDV       1     4              0
## 172 Network           0 self$bipartite_rsienaDV      12     3              0
## 173 Network           0 self$bipartite_rsienaDV      11     5              0
## 174 Network           0 self$bipartite_rsienaDV      12     6              0
## 175 Network           0 self$bipartite_rsienaDV       4     1              0
## 176 Network           0 self$bipartite_rsienaDV       6    10              0
## 177 Network           0 self$bipartite_rsienaDV       8     6              0
## 178 Network           0 self$bipartite_rsienaDV       4     9              0
## 179 Network           0 self$bipartite_rsienaDV       9    10              0
## 180 Network           0 self$bipartite_rsienaDV       4     8              0
## 181 Network           0 self$bipartite_rsienaDV       8    10              0
## 182 Network           0 self$bipartite_rsienaDV       2    10              0
## 183 Network           0 self$bipartite_rsienaDV       9    10              0
## 184 Network           0 self$bipartite_rsienaDV       6     9              0
## 185 Network           0 self$bipartite_rsienaDV       8     7              0
## 186 Network           0 self$bipartite_rsienaDV       1     1              0
## 187 Network           0 self$bipartite_rsienaDV       4     8              0
## 188 Network           0 self$bipartite_rsienaDV      12     2              0
## 189 Network           0 self$bipartite_rsienaDV      11     9              0
## 190 Network           0 self$bipartite_rsienaDV       9    10              0
## 191 Network           0 self$bipartite_rsienaDV      11     2              0
## 192 Network           0 self$bipartite_rsienaDV       1     8              0
## 193 Network           0 self$bipartite_rsienaDV       6     7              0
## 194 Network           0 self$bipartite_rsienaDV       6     4              0
## 195 Network           0 self$bipartite_rsienaDV       9     2              0
## 196 Network           0 self$bipartite_rsienaDV      11     4              0
## 197 Network           0 self$bipartite_rsienaDV      12     7              0
## 198 Network           0 self$bipartite_rsienaDV       7     5              0
## 199 Network           0 self$bipartite_rsienaDV      11     2              0
## 200 Network           0 self$bipartite_rsienaDV       5     1              0
## 201 Network           0 self$bipartite_rsienaDV       2     7              0
## 202 Network           0 self$bipartite_rsienaDV       6     1              0
## 203 Network           0 self$bipartite_rsienaDV       7     8              0
## 204 Network           0 self$bipartite_rsienaDV       8     9              0
## 205 Network           0 self$bipartite_rsienaDV       2     5              0
## 206 Network           0 self$bipartite_rsienaDV      12    10              0
## 207 Network           0 self$bipartite_rsienaDV       1     8              0
## 208 Network           0 self$bipartite_rsienaDV       9    10              0
## 209 Network           0 self$bipartite_rsienaDV       6     1              0
## 210 Network           0 self$bipartite_rsienaDV      10     8              0
## 211 Network           0 self$bipartite_rsienaDV       6     6              0
## 212 Network           0 self$bipartite_rsienaDV      12     4              0
## 213 Network           0 self$bipartite_rsienaDV       9     2              0
## 214 Network           0 self$bipartite_rsienaDV       4    10              0
## 215 Network           0 self$bipartite_rsienaDV       2     1              0
## 216 Network           0 self$bipartite_rsienaDV      10     9              0
## 217 Network           0 self$bipartite_rsienaDV       9     7              0
## 218 Network           0 self$bipartite_rsienaDV      11     4              0
## 219 Network           0 self$bipartite_rsienaDV       8     4              0
## 220 Network           0 self$bipartite_rsienaDV       3     8              0
## 221 Network           0 self$bipartite_rsienaDV       6     5              0
## 222 Network           0 self$bipartite_rsienaDV       5     8              0
## 223 Network           0 self$bipartite_rsienaDV       8     2              0
## 224 Network           0 self$bipartite_rsienaDV       2     3              0
## 225 Network           0 self$bipartite_rsienaDV      10     5              0
## 226 Network           0 self$bipartite_rsienaDV      10     2              0
## 227 Network           0 self$bipartite_rsienaDV       2     7              0
## 228 Network           0 self$bipartite_rsienaDV       2     6              0
## 229 Network           0 self$bipartite_rsienaDV       3     1              0
## 230 Network           0 self$bipartite_rsienaDV       3     5              0
## 231 Network           0 self$bipartite_rsienaDV       9     9              0
## 232 Network           0 self$bipartite_rsienaDV       9     3              0
## 233 Network           0 self$bipartite_rsienaDV       7     4              0
## 234 Network           0 self$bipartite_rsienaDV       7     2              0
## 235 Network           0 self$bipartite_rsienaDV      12    10              0
## 236 Network           0 self$bipartite_rsienaDV       3     4              0
## 237 Network           0 self$bipartite_rsienaDV       8     3              0
## 238 Network           0 self$bipartite_rsienaDV       6     9              0
## 239 Network           0 self$bipartite_rsienaDV       8     2              0
## 240 Network           0 self$bipartite_rsienaDV       8    10              0
## 241 Network           0 self$bipartite_rsienaDV       3    10              0
## 242 Network           0 self$bipartite_rsienaDV      10     5              0
## 243 Network           0 self$bipartite_rsienaDV       1    10              0
## 244 Network           0 self$bipartite_rsienaDV       8     4              0
## 245 Network           0 self$bipartite_rsienaDV       5     6              0
## 246 Network           0 self$bipartite_rsienaDV      11     4              0
## 247 Network           0 self$bipartite_rsienaDV       2     2              0
## 248 Network           0 self$bipartite_rsienaDV       1     2              0
## 249 Network           0 self$bipartite_rsienaDV       4     2              0
## 250 Network           0 self$bipartite_rsienaDV      10     2              0
## 251 Network           0 self$bipartite_rsienaDV       1     4              0
## 252 Network           0 self$bipartite_rsienaDV      11     2              0
## 253 Network           0 self$bipartite_rsienaDV       9     5              0
## 254 Network           0 self$bipartite_rsienaDV       3     4              0
## 255 Network           0 self$bipartite_rsienaDV       5     2              0
## 256 Network           0 self$bipartite_rsienaDV       5     6              0
## 257 Network           0 self$bipartite_rsienaDV       4     2              0
## 258 Network           0 self$bipartite_rsienaDV       6     9              0
## 259 Network           0 self$bipartite_rsienaDV       8     2              0
## 260 Network           0 self$bipartite_rsienaDV       1     4              0
## 261 Network           0 self$bipartite_rsienaDV       8     6              0
## 262 Network           0 self$bipartite_rsienaDV       1    10              0
## 263 Network           0 self$bipartite_rsienaDV       7     9              0
## 264 Network           0 self$bipartite_rsienaDV       4     4              0
## 265 Network           0 self$bipartite_rsienaDV       3     4              0
## 266 Network           0 self$bipartite_rsienaDV       5     6              0
## 267 Network           0 self$bipartite_rsienaDV       6     7              0
## 268 Network           0 self$bipartite_rsienaDV       5     1              0
## 269 Network           0 self$bipartite_rsienaDV       8    10              0
## 270 Network           0 self$bipartite_rsienaDV      12     6              0
## 271 Network           0 self$bipartite_rsienaDV       7     5              0
## 272 Network           0 self$bipartite_rsienaDV      11     2              0
## 273 Network           0 self$bipartite_rsienaDV       5     4              0
## 274 Network           0 self$bipartite_rsienaDV       9     5              0
## 275 Network           0 self$bipartite_rsienaDV       8     3              0
## 276 Network           0 self$bipartite_rsienaDV      11     5              0
## 277 Network           0 self$bipartite_rsienaDV       1     9              0
## 278 Network           0 self$bipartite_rsienaDV       4     2              0
## 279 Network           0 self$bipartite_rsienaDV      12    10              0
## 280 Network           0 self$bipartite_rsienaDV       5     9              0
## 281 Network           0 self$bipartite_rsienaDV       1     8              0
## 282 Network           0 self$bipartite_rsienaDV      10     1              0
## 283 Network           0 self$bipartite_rsienaDV       2     3              0
## 284 Network           0 self$bipartite_rsienaDV      11     5              0
## 285 Network           0 self$bipartite_rsienaDV       8     6              0
## 286 Network           0 self$bipartite_rsienaDV       9     9              0
## 287 Network           0 self$bipartite_rsienaDV       6     1              0
## 288 Network           0 self$bipartite_rsienaDV       9     7              0
## 289 Network           0 self$bipartite_rsienaDV      10     9              0
## 290 Network           0 self$bipartite_rsienaDV       4     6              0
## 291 Network           0 self$bipartite_rsienaDV       8    10              0
## 292 Network           0 self$bipartite_rsienaDV       8     4              0
## 293 Network           0 self$bipartite_rsienaDV       5     6              0
## 294 Network           0 self$bipartite_rsienaDV       6     5              0
## 295 Network           0 self$bipartite_rsienaDV       1     4              0
## 296 Network           0 self$bipartite_rsienaDV      12    10              0
## 297 Network           0 self$bipartite_rsienaDV       1     4              0
## 298 Network           0 self$bipartite_rsienaDV       9     5              0
## 299 Network           0 self$bipartite_rsienaDV      10     5              0
## 300 Network           0 self$bipartite_rsienaDV       7     2              0
##     reciprocal_rate LogOptionSetProb LogChoiceProb diagonal stability
## 1        0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 2        0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 3        0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 4        0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 5        0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 6        0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 7        0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 8        0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 9        0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 10       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 11       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 12       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 13       0.08333333        -2.484907     -2.036973    FALSE      TRUE
## 14       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 15       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 16       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 17       0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 18       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 19       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 20       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 21       0.08333333        -2.484907     -2.036973    FALSE      TRUE
## 22       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 23       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 24       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 25       0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 26       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 27       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 28       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 29       0.08333333        -2.484907     -2.036973    FALSE      TRUE
## 30       0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 31       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 32       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 33       0.08333333        -2.484907     -2.036973    FALSE      TRUE
## 34       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 35       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 36       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 37       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 38       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 39       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 40       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 41       0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 42       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 43       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 44       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 45       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 46       0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 47       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 48       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 49       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 50       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 51       0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 52       0.08333333        -2.484907     -2.036973    FALSE      TRUE
## 53       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 54       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 55       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 56       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 57       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 58       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 59       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 60       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 61       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 62       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 63       0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 64       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 65       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 66       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 67       0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 68       0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 69       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 70       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 71       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 72       0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 73       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 74       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 75       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 76       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 77       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 78       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 79       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 80       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 81       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 82       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 83       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 84       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 85       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 86       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 87       0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 88       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 89       0.08333333        -2.484907     -2.036973    FALSE      TRUE
## 90       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 91       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 92       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 93       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 94       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 95       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 96       0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 97       0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 98       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 99       0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 100      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 101      0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 102      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 103      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 104      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 105      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 106      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 107      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 108      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 109      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 110      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 111      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 112      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 113      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 114      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 115      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 116      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 117      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 118      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 119      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 120      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 121      0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 122      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 123      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 124      0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 125      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 126      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 127      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 128      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 129      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 130      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 131      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 132      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 133      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 134      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 135      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 136      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 137      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 138      0.08333333        -2.484907     -2.036973    FALSE      TRUE
## 139      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 140      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 141      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 142      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 143      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 144      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 145      0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 146      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 147      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 148      0.08333333        -2.484907     -2.036973    FALSE      TRUE
## 149      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 150      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 151      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 152      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 153      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 154      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 155      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 156      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 157      0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 158      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 159      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 160      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 161      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 162      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 163      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 164      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 165      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 166      0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 167      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 168      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 169      0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 170      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 171      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 172      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 173      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 174      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 175      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 176      0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 177      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 178      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 179      0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 180      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 181      0.08333333        -2.484907     -2.036973    FALSE      TRUE
## 182      0.08333333        -2.484907     -2.036973    FALSE      TRUE
## 183      0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 184      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 185      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 186      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 187      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 188      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 189      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 190      0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 191      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 192      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 193      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 194      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 195      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 196      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 197      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 198      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 199      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 200      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 201      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 202      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 203      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 204      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 205      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 206      0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 207      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 208      0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 209      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 210      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 211      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 212      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 213      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 214      0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 215      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 216      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 217      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 218      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 219      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 220      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 221      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 222      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 223      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 224      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 225      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 226      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 227      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 228      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 229      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 230      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 231      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 232      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 233      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 234      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 235      0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 236      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 237      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 238      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 239      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 240      0.08333333        -2.484907     -2.036973    FALSE      TRUE
## 241      0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 242      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 243      0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 244      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 245      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 246      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 247      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 248      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 249      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 250      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 251      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 252      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 253      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 254      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 255      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 256      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 257      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 258      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 259      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 260      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 261      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 262      0.08333333        -2.484907     -1.950596    FALSE      TRUE
## 263      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 264      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 265      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 266      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 267      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 268      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 269      0.08333333        -2.484907     -2.036973    FALSE      TRUE
## 270      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 271      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 272      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 273      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 274      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 275      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 276      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 277      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 278      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 279      0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 280      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 281      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 282      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 283      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 284      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 285      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 286      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 287      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 288      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 289      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 290      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 291      0.08333333        -2.484907     -2.036973    FALSE      TRUE
## 292      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 293      0.08333333        -2.484907     -2.336973    FALSE     FALSE
## 294      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 295      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 296      0.08333333        -2.484907     -2.124484    FALSE      TRUE
## 297      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 298      0.08333333        -2.484907     -2.324484    FALSE     FALSE
## 299      0.08333333        -2.484907     -2.350596    FALSE     FALSE
## 300      0.08333333        -2.484907     -2.350596    FALSE     FALSE
##     tie_change chain_step_id
## 1         TRUE             1
## 2         TRUE             2
## 3         TRUE             3
## 4         TRUE             4
## 5         TRUE             5
## 6        FALSE             5
## 7         TRUE             7
## 8         TRUE             8
## 9         TRUE             9
## 10        TRUE            10
## 11        TRUE            11
## 12        TRUE            12
## 13       FALSE            12
## 14        TRUE            14
## 15        TRUE            15
## 16        TRUE            16
## 17       FALSE            16
## 18        TRUE            18
## 19        TRUE            19
## 20        TRUE            20
## 21       FALSE            20
## 22        TRUE            22
## 23        TRUE            23
## 24        TRUE            24
## 25       FALSE            24
## 26        TRUE            26
## 27        TRUE            27
## 28        TRUE            28
## 29       FALSE            28
## 30       FALSE            28
## 31        TRUE            31
## 32        TRUE            32
## 33       FALSE            32
## 34        TRUE            34
## 35        TRUE            35
## 36        TRUE            36
## 37        TRUE            37
## 38        TRUE            38
## 39        TRUE            39
## 40        TRUE            40
## 41       FALSE            40
## 42        TRUE            42
## 43        TRUE            43
## 44        TRUE            44
## 45        TRUE            45
## 46       FALSE            45
## 47        TRUE            47
## 48        TRUE            48
## 49        TRUE            49
## 50        TRUE            50
## 51       FALSE            50
## 52       FALSE            50
## 53        TRUE            53
## 54        TRUE            54
## 55        TRUE            55
## 56        TRUE            56
## 57        TRUE            57
## 58        TRUE            58
## 59        TRUE            59
## 60        TRUE            60
## 61        TRUE            61
## 62        TRUE            62
## 63       FALSE            62
## 64        TRUE            64
## 65        TRUE            65
## 66        TRUE            66
## 67       FALSE            66
## 68       FALSE            66
## 69        TRUE            69
## 70        TRUE            70
## 71        TRUE            71
## 72       FALSE            71
## 73        TRUE            73
## 74        TRUE            74
## 75        TRUE            75
## 76        TRUE            76
## 77        TRUE            77
## 78        TRUE            78
## 79        TRUE            79
## 80        TRUE            80
## 81        TRUE            81
## 82        TRUE            82
## 83        TRUE            83
## 84        TRUE            84
## 85        TRUE            85
## 86        TRUE            86
## 87       FALSE            86
## 88        TRUE            88
## 89       FALSE            88
## 90        TRUE            90
## 91        TRUE            91
## 92        TRUE            92
## 93        TRUE            93
## 94        TRUE            94
## 95        TRUE            95
## 96        TRUE            96
## 97        TRUE            97
## 98        TRUE            98
## 99        TRUE            99
## 100       TRUE           100
## 101      FALSE           100
## 102       TRUE           102
## 103       TRUE           103
## 104       TRUE           104
## 105       TRUE           105
## 106       TRUE           106
## 107       TRUE           107
## 108       TRUE           108
## 109       TRUE           109
## 110       TRUE           110
## 111       TRUE           111
## 112       TRUE           112
## 113       TRUE           113
## 114       TRUE           114
## 115       TRUE           115
## 116       TRUE           116
## 117       TRUE           117
## 118       TRUE           118
## 119       TRUE           119
## 120       TRUE           120
## 121      FALSE           120
## 122       TRUE           122
## 123       TRUE           123
## 124      FALSE           123
## 125       TRUE           125
## 126       TRUE           126
## 127       TRUE           127
## 128       TRUE           128
## 129       TRUE           129
## 130       TRUE           130
## 131       TRUE           131
## 132       TRUE           132
## 133       TRUE           133
## 134       TRUE           134
## 135       TRUE           135
## 136       TRUE           136
## 137       TRUE           137
## 138      FALSE           137
## 139       TRUE           139
## 140       TRUE           140
## 141       TRUE           141
## 142       TRUE           142
## 143       TRUE           143
## 144       TRUE           144
## 145      FALSE           144
## 146       TRUE           146
## 147       TRUE           147
## 148      FALSE           147
## 149       TRUE           149
## 150       TRUE           150
## 151       TRUE           151
## 152       TRUE           152
## 153       TRUE           153
## 154       TRUE           154
## 155       TRUE           155
## 156       TRUE           156
## 157      FALSE           156
## 158       TRUE           158
## 159       TRUE           159
## 160       TRUE           160
## 161       TRUE           161
## 162       TRUE           162
## 163       TRUE           163
## 164       TRUE           164
## 165       TRUE           165
## 166      FALSE           165
## 167       TRUE           167
## 168       TRUE           168
## 169      FALSE           168
## 170       TRUE           170
## 171       TRUE           171
## 172       TRUE           172
## 173       TRUE           173
## 174       TRUE           174
## 175       TRUE           175
## 176      FALSE           175
## 177       TRUE           177
## 178       TRUE           178
## 179      FALSE           178
## 180       TRUE           180
## 181      FALSE           180
## 182      FALSE           180
## 183      FALSE           180
## 184       TRUE           184
## 185       TRUE           185
## 186       TRUE           186
## 187       TRUE           187
## 188       TRUE           188
## 189       TRUE           189
## 190      FALSE           189
## 191       TRUE           191
## 192       TRUE           192
## 193       TRUE           193
## 194       TRUE           194
## 195       TRUE           195
## 196       TRUE           196
## 197       TRUE           197
## 198       TRUE           198
## 199       TRUE           199
## 200       TRUE           200
## 201       TRUE           201
## 202       TRUE           202
## 203       TRUE           203
## 204       TRUE           204
## 205       TRUE           205
## 206      FALSE           205
## 207       TRUE           207
## 208      FALSE           207
## 209       TRUE           209
## 210       TRUE           210
## 211       TRUE           211
## 212       TRUE           212
## 213       TRUE           213
## 214      FALSE           213
## 215       TRUE           215
## 216       TRUE           216
## 217       TRUE           217
## 218       TRUE           218
## 219       TRUE           219
## 220       TRUE           220
## 221       TRUE           221
## 222       TRUE           222
## 223       TRUE           223
## 224       TRUE           224
## 225       TRUE           225
## 226       TRUE           226
## 227       TRUE           227
## 228       TRUE           228
## 229       TRUE           229
## 230       TRUE           230
## 231       TRUE           231
## 232       TRUE           232
## 233       TRUE           233
## 234       TRUE           234
## 235      FALSE           234
## 236       TRUE           236
## 237       TRUE           237
## 238       TRUE           238
## 239       TRUE           239
## 240      FALSE           239
## 241      FALSE           239
## 242       TRUE           242
## 243      FALSE           242
## 244       TRUE           244
## 245       TRUE           245
## 246       TRUE           246
## 247       TRUE           247
## 248       TRUE           248
## 249       TRUE           249
## 250       TRUE           250
## 251       TRUE           251
## 252       TRUE           252
## 253       TRUE           253
## 254       TRUE           254
## 255       TRUE           255
## 256       TRUE           256
## 257       TRUE           257
## 258       TRUE           258
## 259       TRUE           259
## 260       TRUE           260
## 261       TRUE           261
## 262      FALSE           261
## 263       TRUE           263
## 264       TRUE           264
## 265       TRUE           265
## 266       TRUE           266
## 267       TRUE           267
## 268       TRUE           268
## 269      FALSE           268
## 270       TRUE           270
## 271       TRUE           271
## 272       TRUE           272
## 273       TRUE           273
## 274       TRUE           274
## 275       TRUE           275
## 276       TRUE           276
## 277       TRUE           277
## 278       TRUE           278
## 279      FALSE           278
## 280       TRUE           280
## 281       TRUE           281
## 282       TRUE           282
## 283       TRUE           283
## 284       TRUE           284
## 285       TRUE           285
## 286       TRUE           286
## 287       TRUE           287
## 288       TRUE           288
## 289       TRUE           289
## 290       TRUE           290
## 291      FALSE           290
## 292       TRUE           292
## 293       TRUE           293
## 294       TRUE           294
## 295       TRUE           295
## 296      FALSE           295
## 297       TRUE           297
## 298       TRUE           298
## 299       TRUE           299
## 300       TRUE           300
## 
##  33.33%
##  66.67%
##  100.00%
## =====================================================================================================
##                                                                                 Model 1              
## -----------------------------------------------------------------------------------------------------
## Rate parameter period 1                                                           0.0792 (0.0787)    
## outdegree (density)                                                              -0.5000 (0.0000) ***
## indegree - popularity                                                             0.1000 (0.0000) ***
## outdegree - activity                                                              0.1000 (0.0000) ***
## XW=>X closure of self$component_1_coDyadCovar                                     1.0000 (0.0000) ***
## self$component_2_coDyadCovar                                                      0.0000 (0.0000)    
## self$strat_1_coCovar ego                                                          0.1000 (0.0000) ***
## ind. pop.^(1/0.1) weighted self$strat_2_coCovar                                   0.1000 (0.0000) ***
## self$strat_1_coCovar ego x XW=>X closure of self$component_1_coDyadCovar          0.5000 (0.0000) ***
## ind. pop.^(1/0.1) weighted self$strat_2_coCovar x self$component_2_coDyadCovar    0.5000 (0.0000) ***
## -----------------------------------------------------------------------------------------------------
## Iterations                                                                      300                  
## =====================================================================================================
## *** p < 0.001; ** p < 0.01; * p < 0.05

2.5 Plot Actor Degrees (Component Scope and Common Affiliation Social Ties)

Time series is simulated decision steps.

##
env2$plot_actor_degrees(loess_span = 0.25)
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'

2.6 Plot Component Degrees (Membership/Popularity and Common Actor Epistasis Ties)

##
env2$plot_component_degrees(loess_span = 0.35)
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'

2.7 Plot Utility by Strategy over Time (Simulated Decision Steps)

## [1] 3600    5
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'

2.8 Plot Utility by Actor over Time (Simulated Decision Steps)

## [1] 3600    5
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'

2.9 Plot Contributions to Actor Utility colored by Strategy

Time series is simulated decision steps.

##
env2$plot_utility_components(loess_span=0.35)
## `geom_smooth()` using formula = 'y ~ x'

2.10 Plot Actor Utility Timeseries and Distribution by Strategy

env2$plot_actor_utility_strategy_summary()

2.11 Fitness Landscape Peaks Distribution

Number of changes to component ties as distance from counterfactual affiliation configurations

## Use random uniform values for all combinations like traditional NK model
env2$compute_fitness_landscape(component_coCovar=NA)
## 
## The mean number of peaks per landscape is: 76 
## 
## The std. deviation of the number of peaks per landscape is: 22.50517 
## 
## The skewness of the number of peaks per landscape is: 0.1039261 
## 
## The kurtosis of the number of peaks per landscape is: 0.3387823 
## 
## Elapsed time: 2.88 sec
## Use the component values as the means of random noise for different payoff combinations 
# env2$compute_fitness_landscape(component_coCovar=1)
## LOWER SD of component values noise for different payoff combinations 
# env2$compute_fitness_landscape(component_coCovar=1, component_value_sd=0.01)
## HIGHER SD of component values noise for different payoff combinations 
# env2$compute_fitness_landscape(component_coCovar=1, component_value_sd=0.5)
## 1st and last state of the bipartite matrix system
# dim(env1$fitness_landscape)

hist(env2$fitness_landscape[ 1, , dim(env2$fitness_landscape)[3]-1 ],
     main='Fitness Distribution of Landscape Draw 1', xlab='Fitness')

hist(env2$fitness_landscape[ 1, , dim(env2$fitness_landscape)[3] ],
     main='Peaks Distribution over configurations in Landscape Draw 1', xlab='Peak')

End.